JP7002681B2 - Logical segmentation data processing system - Google Patents

Description

Regarding logical segmentation data processing system.

Geocaching applications include augmented reality and location-based applications that use Global Positioning System (GPS) data for one or more features of the application. Geocaching applications determine the geographic location of the device operating the application. The geocaching application can specify GPS coordinates in the vicinity that correspond to the characteristics of the geocaching application. A geocaching application may allow the user of the application to interact with the feature when the user's device is near a specified coordinate.

The data processing system described in this document offers one or more of the following advantages: The data processing system loads the traffic of people between geopoints (for example, the targeted encouragement location of the geocaching data system) by the geocaching data system segmenting the geographic map into geoareas. Allows to be dispersed. Users of the geocaching data system are attracted to the geopoints of the geocaching data system. Participants in geocaching data system applications (eg, geocaching location owners) want to attract geocaching data system users to their geographic location by being at a geopoint location. Unlike websites, geographic locations are constrained by the permissible load for the geographic location (eg, the amount of traffic) and the user's proximity to the geographic location. Data processing systems allow geographic locations to attract a manageable load by segmenting geographic locations into geoareas. The data processing system selects (for example, encourages) a particular geographic location in the geoarea to be the geopoint of the geocaching data system and attracts users of the geocaching data system to that geographic location.

The data processing system manages the load for geopoints (eg, encouraged geographic locations) by adjusting how often geolocations are selected as geopoints. The data processing system limits the choice of geopoints so that users of the geocaching data system have the opportunity to visit their geographic location, but geopoints frequently enough so that they are not boring to the user. You may update.

By segmenting the map into geoareas, the data processing system allows a geographic location to compete only with other nearby geographic locations in an attempt to become a geopoint in a geocaching data system. Geographic locations are therefore competing for a locally manageable audience.

The data processing system allows the geocaching data system to select geopoints that are of interest to the user of the geocaching data system. Data processing systems allow geocaching data systems to encourage geographic locations that serve users and are more likely to be visited by users compared to other geographic locations. Associate the geographic location with the quality score you want to do.

The data processing system improves the quality of the geocaching data system by allowing the geocaching data system to select geographic locations that are both interesting and useful to the user. The geographic location selected as the geopoint can serve the user attracted by the geopoint in the geocaching data system.

The logical segmented data processing system is a data retrieval interface that receives geocaching data representing the geocaching location specified by the remote geocaching data system from the remote geocaching data system, and the geographic location represented by the geocaching data. A storage for storing quality score data for each of the, and a logical segmentation engine that segments the geographic map into geoareas, each geoarea containing a subset of the geolocation represented by the geocaching data. The logical segmentation engine identifies the size of a geoarea by executing an executable logic that identifies one or more parameter values that constrain the physical load in the geoarea to follow a specified value. A logical segmentation engine and a rating engine that ranks the geographic location of a geoarea for each of multiple geoareas, where each geographic location is scored with a qualified value and the ranking is geographic location. A function of the eligibility value of, each of which is weighted based on quality score data for each of the geographic locations, from the rating engine and each of the multiple geoareas in the geoarea ranking. Select a geographic location that has a higher rank compared to one or more other ranks of one or more other geographic locations, as well as a selected geography that has a higher rank. Includes an aggregation engine that further aggregates target locations.

In some implementations, the aggregation engine generates geopoint data by generating geopoints for each coordinate of the selected geographic location, which has a higher rank, and the geopoint data is remote geo. Send to the caching data system.

In some implementations, each geopoint in geopoint data is associated with data that represents one or more interactive features accessible by a terminal device configured to communicate with a remote geocaching data system.

In some implementations, storage includes a database that stores activity data associated with each of the geocaching locations represented by geocaching data, where activity data has one or more interactive features, remote geo. Caching Represents how often it is accessed by one or more terminal devices configured to communicate with the data system.

In some implementations, the eligibility values are each weighted proportionally to a value that represents the amount of activity indicated by the activity data for each of the geographic locations.

In some implementations, the data processing system includes a timing engine for the geoarea where the evaluation engine determines the evaluation schedule for ranking multiple geographic locations. In some implementations, the timing engine determines the duration according to the evaluation schedule. In some implementations, the logical segmentation engine segments the geographic map into alternative geoareas at least once during the duration.

In some implementations, quality score data for a geographic location represents the probability that a terminal device configured to communicate with a remote geocaching data system will request the data associated with the geographic location. In some implementations, quality score data is based on the length of time the terminal device requests the data associated with the geographic location.

In some implementations, the logical segmentation engine further determines the size of the geoarea based on the number of geographic locations represented by the geocaching data. In some implementations, each geoarea contains a predetermined number of geographic locations.

In some implementations, geocaching data represents a geocaching location from a remote geocaching data system and another remote geocaching data system, and the aggregation engine is a remote geocaching data system and another remote geocaching data system. Send geopoint data to.

In some implementations, each geographic location specified by the remote geocaching data system is associated with a tier score for the geographic location, and the fitness value for the geographic location is weighted in proportion to the tier score. Will be done. In some implementations, the tier score is a first tier that shows the interactive features for the remote geocaching data system associated with the geographic location, including time-based rewards, interactive features for the remote geocaching data system. Specifies the conversion quality of the geographic location, including a second tier that indicates, and one of the third tiers that demonstrate interactive features for remote geocaching data systems, including transactions at the geocaching location.

In some embodiments, the data processing system receives geocaching data from the remote geocaching data system, which represents the geographic location specified by the remote geocaching data system, through a data retrieval interface, and the geocaching data. To store quality score data for each of the geographic locations represented by, and to segment the geographic map into geoareas, where each geoarea is a subset of the geographic locations represented by geocaching data. Identifying the size of a geoarea by performing an executable logic that identifies one or more parameter values that constrain the physical load in the geoarea to follow a specified value. , For each of multiple geoareas, to rank the geographic location of that geoarea, where each geographic location is scored with an eligibility value, and ranking is a function of the eligibility value of the geographic location. And each eligibility value is weighted based on quality score data for each of the geographic locations, and from each of the multiple geoareas, one or more in the ranking of the geoareas. To select a geographic location that has a higher rank compared to one or more other ranks of a geographic location, and to further aggregate the selected geographic locations that have a higher rank. Perform operations including.

Details of one or more embodiments are given in the accompanying drawings and in the description below. Other features, objectives, and advantages of the techniques described herein will become apparent from these descriptions and drawings, as well as the claims.

It is a conceptual diagram of a networked environment for a logical segmented data processing system. It is a diagram of the evaluation process. A geographic map for logical segmented data processing. A geographic map for logical segmented data processing. A geographic map for logical segmented data processing. It is a figure which shows the action taken for the logical segmentation data processing. It is a flow chart which shows the action taken for the logical segmentation data processing. It is a block diagram of the component of the system for logical segmentation data processing.

Similar reference numerals in various drawings indicate similar elements.

This document describes a data processing system for logical segmented data processing. For example, a data processing system segments a geographic area (or map) into various segmented parts or areas (referred to herein as "geoareas"). The data processing system, as described in more detail below, by performing executable logic that identifies one or more parameter values that constrain the physical load in the geoarea to follow specified values. Identify the size of the geoarea. By doing so, the data processing system assumes that rendering of the content (for example, on the display device of a terminal device located within the geoarea) creates an acceptable amount of physical load for the geopoints in the geoarea. Save resources (eg, bandwidth, memory consumption and data processing cycles and resources) by limiting to the specified amount. For example, the load on each geopoint is distributed so that a manageable number of users are requesting data related to the geopoint.

The data processing system receives data from one or more geocaching data systems and sends the data to it. Geocaching data includes location-based augmented reality applications. Geocaching data systems include geopoints. Geopoints correspond to GPS coordinates on the geographic map. The data processing system selects the GPS coordinates of the geographic location for the geopoint of the geocaching data system. Geographical locations include physical locations that provide products, services, or both. In some implementations, the geographic location includes stores. The data processing system segments the geographic location into geoareas. The data processing system selects the GPS coordinates of at least one geographic location for each geoarea to correspond to the geopoints of the geocaching data system.

Geopoints include features of geocaching data systems. A user of a geocaching data system can interact with features of a geocaching data system when the user is physically at or near the GPS coordinates of the geopoint (eg, within its distance threshold). A feature of a geocaching data system can include an interactive aspect of the geocaching data system that provides an incentive for the user to visit the geopoint containing the feature. In some implementations, the application of the geocaching data system is a game, and the feature is how the user interacts with and plays with the game. For example, features may include application resources, checkpoints, objectives, or other interactive aspects. In some implementations, the features for each geopoint are unique. Users of the geocaching data system are attracted to the geopoint because they can interact with the features of the geocaching data system at the geopoint.

Geopoints therefore provide incentives for users to visit the geographic location associated with the geopoint (eg, a store). In some implementations, increased load on geographic locations (eg, traffic) correlates with increased sales of products or services at geographic locations, increased brand awareness, increased interest in geographic locations, and so on. .. Data processing systems allow geographic locations to become geopoints in geocaching data system applications and thus compete to benefit from increased load.

Data processing systems allow geocaching data systems to load balance across geopoints by segmenting geographic maps into geoareas. Unlike web locations (eg websites, online stores, etc.), geographic locations constrain the permissible load for the geographic location (eg, the amount of traffic) and the user's proximity to the geographic location. To. A data processing system allows a geographic location to attract a manageable load by segmenting a geographic map containing the geographic location into geoareas for a specified time period. The data processing system uses the data provided by the geocaching data system, such as activity data about the geographic location, to segment the geographic map into geoareas. The data processing system segments the timeline into evaluation periods. The data processing system selects geopoints at a frequency indicating the evaluation period (eg, once per period) to further manage the load at each geopoint, as described below.

Each geolocation system can provide the data processing system with an appropriate value (eg, bid price) to compete to associate each geolocation with a geopoint in the geocaching data system. .. The data processing system selects geographic locations that may be of interest to users of the geocaching data system. The data processing system therefore allows the geocaching data system to attract a manageable load to the geographic location at the geopoint for each geoarea over a specified time period. Data processing systems allow geocaching data systems to contain geopoints that are of interest to the user, and are realistic for geographic locations but geo-occurringly to keep users interested in geocaching data system applications. Select a point.

Referring to FIG. 1, a logical segmented data processing system in which the networked environment 100 is configured to communicate with the geocaching data system 104 and the qualified value data system 108 (eg, using network 110). Hereinafter, the data processing system 102) is included. The networked environment 100 includes a terminal device 106 configured to communicate with the geocaching data system 104 over the network 110. Each of the data processing system 102, the geocaching data system 104, and the eligibility value system 108 may include one or more computing systems, and a server system.

The data processing system 102 communicates with the geocaching data system 104 via the network 110. The data processing system 102 receives the geocaching data 116 from the geocaching data system 104. In some implementations, the data processing system 102 receives geocaching data 116 through interface 120. The geocaching data system 104 may include an application programming interface (API) that allows the data processing system 102 to access the geocaching data 116 from the geocaching data system 104. The data processing system 102 uses the geocaching data 116 to perform the evaluation and generate the geopoint data 118 representing the geopoints used by the geocaching data system 104.

The geocaching data 116 includes data from the geocaching data system 104 that is used by the data processing system 102 to generate geopoint data 118 for the geocaching data system 104. Geocaching data 116 includes data indicating how many latent geopoints should be in the geographic map for the geocaching data system 104. In some implementations, geocaching data 116 includes a list of geographic locations participating as latent geopoints. Geocaching data 116 includes location activity data for each of the geographic locations. Activity data shows how many users visit one or more of the geographic locations. For example, activity data may indicate that a given number of users have visited a geographic location during a specified amount of time when the geographic location contained geopoints. Activity data is collected by the geocaching data system 104 from the terminal device 106 in which the application of the geocaching data system 104 is installed. Terminal device 106 provides location data 114 to the geocaching data system 104. The geocaching data system 104 records the popularity of each geopoint in a geographic location and can include this information in activity data. In some implementations, the location data 114, when received by the data processing system 102, is anonymized and associated with the geolocation in the location activity data cache 138 of the data processing system 102.

Geocaching data 116 may include information about each of the geographic locations registered in the geocaching data system 104. For example, geocaching data 116 may include a type for each geographic location. Geographical locations can include restaurants, retail stores, transportation hubs, museums, and the like. In some implementations, a geographic location is associated with another geographic location (eg, under a brand name, co-owner, etc.). The data processing system 102 can use geocaching data 116 to assign or update quality scores for geographic locations, as described below.

The data processing system 102 receives the geocaching data 116 from the geocaching data system 104 and generates geopoint data 118 for sending to the geocaching data system 104. To generate the geopoint data 118, the data processing system 102 may perform segmentation, evaluation, and aggregation operations.

The data processing system 102 uses the logical segmentation engine 126 to perform the segmentation operation. The segmentation engine 126 segments a geographic map consisting of geocaching data 116 into geoareas. The geographic map is load balanced among different geopoints and segmented to efficiently distribute the geopoints within the geographic map according to one or more distribution parameters. The distribution parameter is any parameter that can affect the expected level of user demand associated with that geoarea, such as the level of customer foot and / or the time that the user spends at a location within the geoarea. May be understood. Dispersion parameters include metrics such as geopoint density for geographic maps, load levels from activity data, population density, and so on. The allocation of geopoints within an area itself can affect the level of interest of the user in that area, so the number and / or density of geopoints in a particular area is also seen as an example of a distribution parameter. Note that it can be done.

The segmentation engine 126 can use a variety of techniques to segment a geographic map into geographic areas (“geoareas”). The segmentation engine 126 can, for example, segment a geographic map to produce geoareas of approximately equal size. For example, a segmentation engine may specify that each geoarea is one square kilometer, acre, or other size. The segmentation engine 126 can segment a geographic map, for example, to generate geoareas that contain equal or nearly equal numbers of geographic locations. For example, the geocaching data system 104 can register a geographic location as a latent geopoint. The registered geographic location is put into geocaching data 116 and passed to the data processing system 102. The data processing system 102 may segment the geographic map into geoareas, for example, such that each geoarea contains an equal or nearly equal number of registered geographic areas.

The data processing system 102 can register a geographic location that should be considered a geopoint through interface 120. For example, the cartographic application associated with the data processing system 102 can automatically include the geographic location registered with the cartographic application as a latent geopoint. In some implementations, the geographic location is considered a geopoint for the geocaching data system 104 and other similar geocaching data systems that are different from the geocaching data system 104, so that the data processing system You can register directly with 102. The data processing system 102 can combine each list of geographic locations and segment the geographic map to include approximately equal numbers of geographic locations within each geoarea.

The segmentation engine 126 may segment the geographic map according to the activity data in the location activity data cache 138. The activity data is part of the geocaching data 116. As mentioned above, activity data may include data indicating how many terminal devices interacted with features at the geopoints of the geocaching data system 104. The data processing system 102 can collect activity data through the interface 120 using another application, such as the navigation application associated with the data processing system 102. For example, the data processing system 102 makes direct contact with the terminal device 106 to determine which geographic location the terminal device is in close proximity to. In some implementations, the data processing system 102 can collect activity data directly from a geographic location, such as through a registration interface.

The segmentation engine 126 describes which areas of the geographic map are more active than the other areas of the geographic map (ie, for example, which areas attract more people, or which areas have more users. Use activity data to determine if you spend your time). The segmentation engine 126 can divide the more active area into more geoareas so that more geopoints are located in the more active area in order to achieve the load balancing effect.

The segmentation engine 126 may receive metadata associated with each geographic location, indicating the type for each geographic location. The type of geographic location indicates the service or product of the geographic location. The segmentation engine 126 can segment a geographic map to ensure a diverse selection of geographic location types within each geoarea. In some implementations, two or more geographic locations are associated with each other. The segmentation engine 126 can segment a geographic map to prevent associated geographic locations from being in a common geoarea.

The segmentation engine 126 can segment a geographic map based on quality score data for the geographic location. The quality score data indicates the quality of the geographic location to be the geopoint of the geocaching data system 104. The geographic location quality score is generated by the data processing system 102 based on one or more other data items associated with the geographic location.

Quality scores for geographic locations are based on the type of geographic location. For example, a pedestrian-friendly geographic location may receive a higher quality score. A geographic location that is larger and can accommodate more users may have a higher quality score. The type of product or service in your geographic location can affect your Quality Score. Ratings, reviews, etc. are used to determine the quality score of a geographic location. The activity data for the geographic location is used by the data processing system 102 to determine the quality score for the geographic location. In some implementations, machine learning techniques are used with activity data to determine in which geographic location a user is likely to spend time. In some implementations, the quality score for each geographic location is stored in the quality score cache 140.

The quality score data is adjusted based on the geocaching data 116 received from the geocaching data system 104. For example, if the geocaching data system 104 reports a large number of conversions (eg, purchases) associated with a geopoint, the rating engine 122 may adjust the quality score for the geographic location associated with the geopoint. Quality score data is adjusted based on how long the user spends at geopoints and geographic locations. For example, if a user spends more time at a geopoint, the quality score of the geographic location associated with that geopoint is increased. The data processing system 102 may use the data received directly from the terminal device 106 to determine the duration of the visit to the geographic location and adjust the quality score accordingly. In some implementations, the duration of user visits and the type of geographic location are used together to adjust the quality score of the geographic location. For example, a user may spend more time in a restaurant than in a coffee shop.

The segmentation engine 126 can segment the geographic map so that each geoarea contains a geographic location with a threshold quality score. The segmentation engine 126 can therefore ensure that a minimum number of quality geographic locations are available in the geoarea that should be the geopoint of the geocaching data system 104. In some implementations, the duration of user visits and the type of geographic location are used together to adjust the quality score of the geographic location. For example, a user may spend more time in a restaurant than in a coffee shop. The frequency of returning to geopoints can also be considered. For example, a user may spend an equal amount of time at a coffee shop and a car oil changer, but is likely to return to the coffee shop more often.

The segmentation engine 126 ensures that the valuation level of user demand for each geoarea is maintained at or below the specified value or "load tolerance", and is a load for the geoarea. Dispersion can be carried out. For example, a geographic area may indicate daily load tolerance, and the segmentation engine may segment the geographic map into geoareas according to the specified load tolerance. In some implementations, load tolerance can be assessed according to population density, type of geographic location, or other data associated with the geographic location. The level of demand for each geoarea can be evaluated based on parameters similar to the distribution parameters discussed above, for example, the level of demand for a particular geoarea is the geopoint density within that geoarea, within that geoarea. It can be judged based on the load level from the activity data of, the population density in the geo area, and so on. The demand valuation level may be expressed as the number of expected visits by users of geocaching data system 104 or other applications associated with data processing system 102. The demand evaluated may be expressed as a value for the geographic location of the geographic map or an average of the specified values.

When the segmentation engine divides the geographic map into geoareas, the geoareas are stored in the geoarea cache 136. Geographical map segmentation is described further below in relation to FIGS. 3A-3C.

Geopoint cache 134, geoarea cache 136, location activity data cache 138, quality score cache 140, and eligibility value cache 142 are key to each geographic location, as well as the type, activity data, for each geographic location. Quality score data, fitness value data, geoarea data, and geopoint data are harmonized to be associated with their respective keys. Data from caches 134, 136, 138, 140, and 142 are used by the evaluation engine 122 during the evaluation process, as described below.

The data processing system 102 is configured to communicate with several qualified value providers, such as the qualified value system 108. The eligibility value system 108 provides the eligibility value data 146 to the data processing system 102 for use by the evaluation engine 122. The eligibility value system 108 includes a system that represents one or more geographic locations. The eligibility value system 108 can use the interface 120 directly to register the geographic location with the data processing system 102. In some implementations, the fitness value system 108 can register the geographic location data 148 with the geocaching data system 104, and the geographic location data 148 is passed to the data processing system 102 with the geocaching data 116. Is done. The data processing system 102 stores the geographic location data 148 in one or more of the caches 134, 136, 138, 140, 142.

The rating engine 122 (eg, ad exchange) of the data processing system 102 performs a rating (eg, auction) for each geoarea to determine which geographic location of the geoarea is associated with the geopoint. The rating engine receives fitness data 146 for one or more geographic locations in the geoarea from the fitness system 108. The eligibility value data 146 includes eligibility values for valuation (eg, bid price). The rating engine 122 uses the suitability value for each geographic location to rank the geographic location for the geoarea. The higher ranked geographic location (eg, the highest ranked location) is selected by the rating engine. The data processing system 102 uses the GPS coordinates of the selected geographic location as geopoints for the geoarea.

The evaluation engine 122 uses data from one or more of the caches 134, 136, 138, 140, and 142 during evaluation. In some implementations, the eligibility value is weighted by the quality score of the quality score cache 140. Quality scores increase the probability that a desirable geographic location will be selected as a geopoint compared to performing an assessment using unweighted eligibility values. Geographic locations with higher quality scores have higher weights than geographic locations with lower quality scores and may be ranked higher by the rating engine 122. In some implementations, the quality score weight is proportional to the score.

Each geoarea contains at least one geopoint that represents the higher (eg, highest) ranked geographic location of the rating. In some implementations, multiple geopoints are selected for each geoarea.

The evaluation engine 122 may perform evaluations on one or more geoareas in parallel to reduce the latency of sending geopoint data 118 to the geocaching data system 104. When a request for geopoint data 118 is received by the data processing system 102, the data processing system 102 either performs an evaluation using the evaluation engine 122 or is preloaded based on an evaluation that has already been performed. The geopoint data 118 can be sent to the geocaching data system 104.

The frequency of geo-area geographic location assessments negatively impacts the load on the geographic location (eg, traffic). The evaluation engine 122 may perform evaluations at specified intervals or at a determined evaluation frequency in order to adjust the load for each geopoint. The data processing system 102 determines that the activity data indicates a decrease in activity at one or more geopoints, and the decrease in activity means that the user has already visited or not visited the geographic location of the geopoint. For example, it indicates a diminished interest in visiting a geographic location, which can affect the quality score and rank of the geographic location in another assessment.

Geographical locations are often interested in being geopoints for a known (eg, given) time period. For example, a geographic location wants to know in advance some time that the geographic location will be associated with the geopoint and for what time period and duration the geographic location will be associated with the geopoint. .. For example, a geographic location may want to be associated with a geopoint during a particular day, time, holiday, time from the beginning of the week, length of time, and so on. A geographic location may want to encourage users to become geopoints in advance, geopoint during regular intervals, etc., in order to invite users to visit the geographic location at the desired time. In some implementations, the evaluation engine 122 uses the eligibility values received from the eligibility value system 108 to perform the evaluation prior to sending the geopoint data 118 to the geocaching data system 104. The rating engine 122 performs an assessment for each geoarea and uses the assessment result data 144 to report which geographic location is the geopoint at which time and duration.

The timing engine 128 regulates the frequency of evaluation by the evaluation engine 122 and the segmentation by the segmentation engine 126 to manage the load for the geopoint. For example, the segmentation engine 126 can specify the duration at which the geoarea is set before another segmentation occurs and give this data to the eligibility value system 108, which is the eligibility value (eg, eligibility value). Bid value) can be affected. An assessment schedule that specifies at what duration the qualification system 108 is sending qualification data 146 and how long the geographic location selected by the valuation engine 122 is associated with the geopoint. Created by the timing engine 128. In some implementations, the evaluation engine 122 performs the evaluation according to an evaluation schedule rather than in response to a request for geopoint data 118 by the geocaching data system 104. For example, the evaluation schedule may specify an evaluation period such as one day or one week, and the evaluation engine 122 performs the evaluation only once for each geoarea for each evaluation period. In some implementations, the geocaching data system 104 may request updated geopoint data 118 at specified intervals. In some implementations, the data processing system 102 determines how often the geopoint data 118 is updated based on the activity data received.

The eligibility value is adjusted by the data processing system 102 based on the duration of the evaluation period and the size of the geoarea. For example, a higher eligibility value for a geographic location corresponds to a longer duration as a geopoint or a larger geoarea associated with the geopoint. The eligibility value is higher for geoareas with a single geopoint and lower for geoareas with multiple geopoints. Eligibility values are higher for larger (eg, more geographic locations) geoareas than for smaller (eg, less geographic locations) geoareas. Eligibility values can be higher for certain time periods, such as days, weeks, and months. For example, the eligibility value system 108 may send higher eligibility values for durations associated with discount hours, weekends, business hours, and so on.

The eligibility value is adjusted by the data processing system 102 and associated with the geopoint based on the tier score of the geocaching data 116. The geocaching data system 104 includes geopoint features with different tiers, depending on the incentives the features create for the user, such as interacting with the geographic location. For example, the lowest tier score indicates a visiting tier. The visit tier is associated with a feature of the geocaching data system 104 that requires the user to visit a geographic location. The middle tier indicates a detour tier. The detour tier is associated with a feature of the geocaching data system 104 that requires the user to visit a geographic location and detour for a minimum duration. For example, this feature may require the user to take a number of threshold steps and wait for a period of time within the threshold distance. Detour tiers create greater incentives for users to interact with geographic locations (eg, buy products or services) than visit tiers. The highest tier indicates the conversion tier. Conversion tiers are associated with features of the geocaching data system 104 that require users to trade (eg, buy) at a geographic location. In some implementations, the eligibility value for higher tiers is higher than the eligibility value for lower tiers. Transactions can be validated by a geocaching app when a user interacts with a Near Field Communication (NFC) beacon, such as by scanning a barcode. The geocaching data system 104 can provide in-game rewards to the user in response to receiving validation data from the data processing system 102.

The rating engine 122 ranks the geographic locations for the geoarea, and the ranked geographic locations are a subset of all the geographic locations on the geographic map. The geographic locations of the subset are ranked according to their respective weighted eligibility scores. Higher-ranked geographic locations are better geographic locations for geopoints for those geoareas than lower-ranked geographic locations. The rating engine 122 ranks the geographic location for each geoarea identified by the segmentation engine 126.

The aggregation engine 130 selects at least one geographic location to identify as a geopoint from each subset of geographic locations, and each subset of geographic locations consists of geographic locations for geoareas. In some implementations, the aggregation engine 130 selects from each geoarea a single geographic location that should be a geopoint. In some implementations, the aggregation engine 130 selects multiple geographic locations that should be geopoints from each geoarea. In some implementations, different numbers of geopoints are selected for different geoareas.

The aggregation engine 130 generates geopoint data 118 indicating the geopoints of the geocaching data system 104 and sends the geopoint data to the geocaching data system 104. In some implementations, geopoint data 118 is associated with a specified time period in which the geopoint associated with the geodata is active in the application of the geocaching data system 104. The aggregation engine 130 may queue the generated geopoint data 118 until a request for geopoint data is received from the geocaching data system 104. In some implementations, the aggregation engine 130 of the data processing system 102 may send the geopoint data 118 to the geocaching data system 104 when the data is generated.

The aggregation engine 130 sends the evaluation result data 144 to the aptitude value system 108. The evaluation result data 144 includes which geographic location is the geopoint and at what time period the geographic location is the geopoint. For example, evaluation result data 144 may include that geographic location A is a geopoint for the geocaching data system 104 on Mondays from 8 am to 5 pm. In some implementations, the fitness value system 108 informs the geographic location of the additional load of having geopoints in the vicinity.

FIG. 2 includes a diagram showing the aggregation process 200. In the case of multiple geocaching data systems requesting geopoint data from the data processing system 102, the aggregation engine may aggregate geopoints across different geocaching data systems. For example, in cases where the geographic location is guaranteed to be the exclusive geopoint of the geoarea, a single assessment is performed by the assessment engine for all geocaching data systems. Geographic locations selected to be geopoints for geocaching data system A may not be selected for geocaching data system B. In addition, the aggregation engine considers load balancing across all geocaching data systems. The aggregation engine takes the cumulative additional load incurred for a geographic location when multiple geopoints are assigned a geographic location, such as geopoint A for geocaching data system A and geopoint B for geocaching data system B. Consider.

In FIG. 2, the geographic location 202 eligibility value system submits two eligibility values: the eligibility value 206 for geocaching data system A and the eligibility value 208 for geocaching data system B. Similarly, the geographic location 204 eligibility system submits an eligibility value 210 for geocaching data system A and an eligibility value 212 for geocaching data system B. Each eligibility value 206, 208, 210, 212 is weighted according to quality score, activity data, etc., as described above in the context of FIG. 1 (214, 216, 218, 220). In some implementations, fitness values are received in the format used for online digital content items (eg, advertising). The interface presented to the system associated with the geographic location may be the same as for the data processing system 102 with respect to other evaluation processes for online digital content items. The weighted eligibility values 222, 224, 226, and 228 are evaluated by the evaluation engine 230. For geocaching data system A, geographic location X will be awarded Geopoint 232. For geocaching data system B, geographic location Y will be awarded geopoint 234. In some implementations, all weighted eligibility values 222, 224, 226, 228 are considered together by the evaluation engine 230 and the eligibility values are adjusted accordingly. In some implementations, separate evaluations are performed for geocaching data system A and geocaching data system B. In this way, a set number of geopoints may be selected across several geocaching data systems so that the geopoints can be load balanced.

3A-3C show exemplary geographic maps 310, 320, and 330 of an application on a terminal device (eg, terminal device 106), respectively. Geographic maps 300, 310, 320 represent the segmentation process performed by the data processing system (eg, data processing system 102 in FIG. 1).

In FIG. 3A, the geographic map 300 shows a plurality of geographic locations 302 represented as pins on the geographic map 300. Only part of the pins are labeled 302, but each pin is a geographic location. The geographic location can be registered with the geocaching data system, with another application associated with the data processing system, or both as described above. The geographic location 302 has a varying density across the geographic map 300. For example, there may be more locations near a commercial zone than in a nearby park or residential area.

FIG. 3B shows a geographic map 302 after being divided into geoareas, for example by a segmentation engine (eg, segmentation engine 126 in FIG. 1). Geoareas 304, 306, 308, 310, 314, 316 are examples of possible geoareas that can be depicted by the segmentation engine. However, other geo-areas are possible. For example, geoareas may be uniform in size, shape, number, etc. of geographic locations, as described above. In this example, geoareas 304, 306, 310, 314, and 316 each contain five geographic locations and geoarea 308 contains two. Geographic location 312 is ranked by a rating engine (eg, rating engine 122 in Figure 1) to determine which geolocation is associated with a geopoint for geoarea 306. Each of the segments 304, 306, 308, 310, 314, 316 can be evaluated in parallel.

Figure 3C shows the geographic map 330 after the evaluation was performed for each geoarea 304, 306, 308, 310, 314, 316. For example, geographic location 318 is a geopoint for geoarea 306, geographic location 320 is a geopoint for geoarea 316, geographic location 322 is a geopoint for geoarea 314, and geographic location 324 is a geoarea. Geopoint for 310. In this example, geopoints 320 and 322 are geographically relatively close to each other compared to other geographic locations. As mentioned above, this may be due to a higher amount of traffic near geographic locations 320, 322, which seeks load balancing to distribute the area between the two geoareas. Geographic location 324 is relatively far from other geopoints. As mentioned above, this may be due to the geoarea 310 having a lower amount of human traffic compared to other geoareas.

FIG. 4 includes FIG. 400 showing the actions taken for logical segmented data processing. The geocaching data system 104 sends geocaching data to the data processing system 102 (402). The data processing system 102 receives the geocaching data (404). Data processing system 102 associates a quality score with the geographic location of geocaching data (406). Data processing system 102 segments the geographic map into geoareas (408). The eligibility value system 108 sends the eligibility value to the data processing system 102. The data processing system 102 weights the eligibility values as described above. Data processing system 102 ranks geographic locations (418). The eligibility value system 108 receives eligibility value data from the data processing system 102 (420). Data processing system 102 aggregates ranked geographic locations to generate geopoint data (422). The geocaching data system 104 receives geopoint data from the data processing system 102 (424). The geocaching data system 104 sends geopoint data to terminal device 106 (426). The terminal device receives geopoint data (428). Users of terminal device 106 can see and interact with geocaching data system applications at geopoints.

Figure 5 shows the process 500 taken for logical segmented data processing. The data processing system (for example, the data processing system 102 in Figure 1) receives geocaching data, including geographic location (502). The data processing system segments the geographic map into geoareas (504). The data processing system associates the qualification value with the quality score (506). The data processing system ranks geographic locations based on weighted eligibility values (508). The data processing system produces geopoint data (510). The data processing system sends geopoint data to the remote geocaching system (512).

FIG. 6 shows exemplary computing devices 600, 650 that can be used to implement the systems and methods described in this document, either as clients or as one or more servers. .. The computing device 600 is intended to represent various forms of digital computers such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The computing device 650 is intended to represent various forms of mobile devices such as personal digital assistants, cellular phones, smartphones, and other similar computing devices. In addition, the computing device 600 or 650 can include a universal serial bus (USB) flash drive. USB flash drives can store operating systems and other applications. A USB flash drive can include input / output components such as a wireless transmitter or USB connector that can be plugged into the USB port of another computing device. The components shown herein, their connections and relationships, and their functions are for illustration purposes only and are intended to limit the embodiments of the invention described and / or claimed herein. Not as.

The computing device 600 includes a high-speed interface 608 that connects to a processor 602, a memory 604, a storage device 606, a memory 604 and a high-speed expansion port 610, and a low-speed interface 612 that connects to the low-speed bus 614 and the storage device 606. Each of the components 602, 604, 606, 608, 610, and 612 may be interconnected using various buses and mounted on a common motherboard or in other ways as needed. Processor 602 includes instructions stored in memory 604 or on storage device 606 for displaying graphical information about the GUI on an external input / output device such as a display 616 coupled to high speed interface 608. It can process instructions for execution within the computing device 600. In other implementations, multiple processors and / or multiple buses may be used with multiple memory and types of memory as needed. Also, multiple computing devices 600 may be connected, with each device providing the required portion of operation (eg, as a server bank, a group of blade servers, or a multiprocessor system).

The memory 604 stores information in the computing device 600. In one implementation, the memory 604 is one or more volatile memory units. In another implementation, the memory 604 is one or more non-volatile memory units. The memory 604 may be another form of computer-readable medium, such as magnetic, computer-readable hardware storage devices, or optical discs.

The storage device 606 is capable of providing high capacity storage to the computing device 600. In one embodiment, the storage device 606 is an array of devices including floppy disk devices, hard disk devices, optical disk devices, or tape devices, flash memory or other similar solid memory devices, or devices in storage area networks or other configurations. Can be computer readable media such as, or include them. Computer program products can be tangibly implemented throughout an information carrier. Computer program products may also contain instructions that, when executed, perform one or more methods as described above. The information carrier is a computer or machine readable medium such as memory 604, storage device 606, or memory on processor 602.

The high speed controller 608 manages the bandwidth consumption type operation for the computing device 600, and the low speed controller 612 manages the bandwidth consumption type operation. Such allocation of functions is only an example. In one implementation, the high speed controller 608 is coupled to memory 604 (eg, through a graphics processor or accelerator), display 616, and fast expansion port 610 that can receive various expansion cards (not shown). .. In this implementation, the slow controller 612 is coupled to the storage device 606 and the slow expansion port 614. The slow expansion port can include various communication ports (eg, USB, Bluetooth®, Ethernet®, Wireless Ethernet®), but one or more such as keyboards, pointing devices, scanners, etc. Can be coupled to an input / output device or a network device such as a switch or router, for example through a network adapter.

The computing device 600 may be implemented in several different ways, as shown in the figure. For example, it can be implemented multiple times as a standard server 620 or in a group of such servers. It can also be implemented as part of the rack server system 624. In addition, it can be implemented on a personal computer such as the laptop computer 622. Alternatively, the components from the computing device 600 can be combined with other components in a mobile device (not shown), such as the device 650. Each such device can include one or more of the computing devices 600, 650, and the entire system can be made up of multiple computing devices 600, 650 communicating with each other.

Compute device 650 includes, among other components, input / output devices such as processor 652, memory 664, display 654, communication interface 666, and transceiver 668. The device 650 may be provided with a storage device such as a microdrive or other device to provide additional storage. Each of the components 650, 652, 664, 654, 666, and 668 is interconnected using various buses, some of which are on a common motherboard or, as needed, others. It may be mounted by the method.

Processor 652 can execute instructions in the computing device 650, including instructions stored in memory 664. The processor may be implemented as a chipset of chips containing separate and multiple analog and digital processors. In addition, the processor can be implemented using any of several architectures. For example, the processor 652 may be a CISC (complex instruction set computer) processor, a RISC (reduced instruction set computer) processor, or a MISC (minimum instruction set computer) processor. The processor can allow coordination of other components of the device 650, such as the user interface, the applications run by the device 650, and the control of wireless communication by the device 650.

The processor 652 can communicate with the user through the control interface 658 and the display interface 656 coupled to the display 654. The display 654 may be, for example, a TFT (thin film transistor liquid crystal display) display or an OLED (organic light emitting diode) display, or other suitable display technology. The display interface 656 may include suitable circuit mechanisms for driving the display 654 to present graphical and other information to the user. The control interface 658 may receive commands from the user and translate them for submission to processor 652. Further, the external interface 662 may communicate with the processor 652 so as to allow short-range communication between the device 650 and other devices. The external interface 662 can provide, for example, wired communication or, in other implementations, wireless communication, and a plurality of interfaces may be used.

The memory 664 stores information in the computing device 650. The memory 664 may be implemented as one or more computer-readable media, one or more volatile memory units, or one or more of one or more non-volatile memory units. Extended memory 674 may be provided and connected to device 650 through extended interface 672, which interface 672 may include, for example, a SIMM (single inline memory module) card interface. Such extended memory 674 can provide extra storage space for device 650, or can also store applications or other information for device 650. In particular, the extended memory 674 can include instructions for practicing or supplementing the process described above, and can also include secure information. Thus, for example, the extended memory 674 may be a security module for the device 650 and may be programmed with instructions permitting the secure use of the device 650. In addition, secure applications may be provided via the SIMM card along with additional information, such as placing identification information on the SIMM card to prevent hacking.

Memory can include, for example, flash memory and / or NVRAM memory, as discussed below. In one implementation, the computer program product is tangibly implemented throughout the information carrier. A computer program product contains instructions that, when executed, perform one or more methods as described above. The information carrier is a computer or machine readable medium such as memory 664, extended memory 674, or memory on processor 652, which may be received via a transceiver 668 or an external interface 662.

The device 650 can communicate wirelessly through a communication interface 666, which may include a digital signal processing circuit mechanism if desired. The communication interface 666, among others, has various modes such as GSM® voice call, SMS, EMS, or MMS message communication, CDMA, TDMA, PDC, WCDMA®, CDMA2000, or GPRS. Alternatively, communication by protocol can be provided. Such communication can occur, for example, through the radio frequency transceiver 668. In addition, short-range communications can occur using, for example, Bluetooth®, WiFi, or other such transceivers (not shown). In addition, the GPS (Global Positioning System) receiver module 670 can provide additional navigation and location-related wireless data to the device 650, which is used by applications running on the device 650 as needed. Can be done.

The device 650 can also communicate audibly using the audio codec 660, which can receive utterance information from the user and convert it into usable digital information. The audio codec 660 can also similarly generate audible sound for the user, for example through a speaker in the handset of the device 650. Such sounds may include sounds from voice calls, may include recorded sounds (eg, voice messages, music files, etc.), and may also include sounds produced by applications running on the device 650. good.

The computing device 650 may be implemented in several different ways, as shown in the figure. For example, it can be implemented as a cellular phone 680. It can also be implemented as part of a smartphone 682, a personal digital assistant, or other similar mobile device.

Various implementations of the systems and techniques described herein include digital electronic circuit mechanisms, integrated circuit mechanisms, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and / or theirs. It can be realized by combination. These various implementations may include implementations in one or more computer programs that are executable and / or translatable on a programmable system that includes at least one programmable processor, the programmable processor being stored. It may be a special or general purpose combined to receive data and instructions from the system, at least one input device, and at least one output device, and to send data and instructions to them.

These computer programs (also known as programs, software, software applications or code) include machine instructions for programmable processors, in highly procedural and / or object-oriented programming languages, and / or in assembly / machine languages. Can be implemented. As used herein, the terms "machine-readable medium" and "computer-readable medium" are used to provide machine instructions and / or data to a programmable processor that includes a machine-readable medium that receives machine instructions as machine-readable signals. Refers to any computer program product, device and / or device used (eg, magnetic disk, disk, memory, programmable logic device (PLD)). The term "machine readable signal" refers to any signal used to provide machine instructions and / or data to a programmable processor.

To enable interaction with the user, the systems and techniques described here include display devices for displaying information to the user (eg, CRT (cathode tube) or LCD (liquid crystal display) monitor) and the user. It can be implemented on a computer that has a keyboard and a pointing device (eg, a mouse or trackball) to give input to the computer. Other types of devices can also be used to enable interaction with the user, for example, the feedback given to the user can be any form of sensory feedback (eg, visual feedback, auditory feedback, or tactile feedback). ), And the input from the user can be received in any form, including acoustic, utterance, or tactile input.

The systems and techniques described herein include back-end components (eg, as data servers), or include middleware components (eg, application servers), or front-end components (eg, systems and techniques described herein). Implemented in a computing system that includes a form of implementation of the technique and a client computer that has a graphical user interface or web browser for user interaction), or any combination of such backends, middleware, or frontend components. be able to. The components of the system can be interconnected by any form or medium of digital data communication (eg, a communication network). Examples of communication networks include local area networks (“LAN”), wide area networks (“WAN”), peer-to-peer networks (with ad hoc or static members), grid computing infrastructure, and the Internet.

The computing system may include clients and servers. Clients and servers are generally separated from each other and usually interact through communication networks. The client-server relationship is generated by a computer program that runs on each computer and has a client-server relationship with each other.

Although some implementation forms have been described in detail above, other modifications are possible. Moreover, other mechanisms for logical data segmentation may be used. Moreover, the logical flows shown in the drawings do not require the specific order or order shown to achieve the desired result. Other steps may be provided, or the steps may be removed from the described flow, and other components may be added to or removed from the described system. Therefore, other implementations are within the scope of the following claims.

100 Networked environment
102 Data processing system
104 Geocaching data system
106 Terminal device
108 Aptitude Value Data System, Appropriate Value System
110 network
120 interface
122 Evaluation engine
126 Logical segmentation engine, segmentation engine
128 Timing engine
130 Aggregate engine
134 Geopoint cash, cash
136 Geoarea cash, cash
138 Location activity data cash, cash
140 Quality Score Cash, Cash
142 Appropriate value cash, cash
230 rating engine
600 computing device
602 processor, component
604 Memory, components
606 Storage device, component
608 High-speed interface, components, high-speed controller
610 High-speed expansion port, component
612 Slow interface, components, slow controller
614 Slow bus, slow expansion port
616 display
620 standard server
622 laptop computer
624 Rack server system
650 Computing devices, devices, components
652 processor, component
654 Display, components
656 display interface
658 Control interface
660 audio codec, codec
662 External interface
664 Memory, components
666 Communication interface, components
668 Transceivers, Components, Radio Frequency Transceivers
670 GPS (Global Positioning System) Receiver Module
672 extended interface, interface
674 Extended memory
680 Cellular phone
682 smartphone

Claims (23)

A logical segmentation data processing system that processes data representing geographic locations for segmentation into subsets.
A data retrieval interface that receives geocaching data representing the geographic location specified by the remote geocaching data system from the remote geocaching data system.
A storage for storing data for each of the geographic locations represented by the geocaching data, wherein the data specifies the number of expected user visits to the geographic location. ,
A logical segmentation engine that segments a geographic map into geoareas based at least in part on the number of expected user visits to the geographic location, where each geoarea is represented by the geocaching data. Each subset of the geographic locations for each geoarea contains a subset of the geographic locations that are less than all within the geoarea, and the segmentation is expected to meet a specified threshold. With a logical segmentation engine, which results in each geoarea with a number of user visits
For each of the plurality of said geoareas, a rating engine that ranks the geographic location of that geoarea, where each geographic location is scored with an appropriate value and the ranking is of the said geographic location. The evaluation engine, which is a function of the eligibility value,
An aggregation engine that selects geopoints from each of the geoareas as locations for presenting interactive features within the geographic map interface of the remote geocaching data system, the selected geopoints being a particular geography. A logical segmented data processing system that includes an aggregation engine that corresponds to the particular geographic location that has a higher rank than at least one other geographic location within the same geoarea as the target location. The aggregation engine generates geopoint data by generating geopoints for each coordinate of the geographic location with a higher rank within each geoarea, and the geopoint data is the remote geocaching data system. The logical segmented data processing system according to claim 1, which is transmitted to. The second aspect of claim 2, wherein each geopoint of the geopoint data is associated with data representing one or more interactive features accessible by a terminal device configured to communicate with the remote geocaching data system. Logical segmented data processing system. The storage includes a database that stores activity data for each of the geographic locations represented by the geocaching data, where the activity data is how often the one or more interactive features feature the remote geo. The logical segmented data processing system of claim 3, which represents whether it is accessed by one or more terminal devices configured to communicate with the caching data system. The logical segmentation data of claim 4, wherein the eligibility value for each of the geographic locations is weighted in proportion to a value representing the amount of activity indicated by the activity data for the geographic location. Processing system. The logical segmentation according to claim 4, further comprising a timing engine, which determines an evaluation schedule for the evaluation engine that specifies how often the plurality of said geographic locations are ranked for the geoarea. Data processing system. The logical segmentation data processing system according to claim 6, wherein the logical segmentation engine segments the geographical map into an alternative geoarea at least once based on the evaluation schedule. The eligibility value for each geographic location is weighted based on the quality score data for the geographic location so that the quality score data for the geographic location communicates with the remote geocaching data system. The logical segmentation data processing system according to claim 1, wherein the configured terminal device represents the probability of requesting data regarding the geographic location. The logical segmentation data processing system of claim 8, wherein the quality score data is based on the length of time the terminal device requests data for the geographic location. The segmentation results in each geoarea having the expected number of user visits by users of the remote geocaching data system below the specified threshold.
The logical segmentation data processing system of claim 1, wherein the logical segmentation engine further determines the size of the geoarea based on the number of geographic locations represented by the geocaching data. The logical segmentation data processing system of claim 1, wherein each geoarea contains less than a predetermined number of geographic locations. The geocaching data represents a geographic location from the remote geocaching data system and another remote geocaching data system, and the aggregation engine is described in the remote geocaching data system and another remote geocaching data system. The logical segmented data processing system according to claim 2, which sends geopoint data. Each geographic location designated by the remote geocaching data system is associated with a tier score for the geographic location, and the eligibility value for the geographic location is weighted in proportion to the tier score. The tier score is
A first tier, which exhibits interactive features for the remote geocaching data system associated with the geographic location, and
A second tier, showing the interactive features for the remote geocaching data system, including time-based rewards,
Claims specifying a conversion type for the geographic location, including one of a third tier, indicating said interactive features for the remote geocaching data system, including transactions at the geographic location. The logical segmented data processing system described in 1. A method for processing data that represents a geographic location for segmentation into subsets.
A step of receiving geocaching data representing the geocaching location specified by the remote geocaching data system from the remote geocaching data system through the data retrieval interface.
A step of storing data for each of the geographic locations represented by the geocaching data, wherein the data specifies the number of expected user visits to the geographic location.
A step of segmenting a geographic map into geoareas based at least in part on the number of expected user visits to the geographic location, where each geoarea is represented by the geocaching data. Each subset of the geographic locations for each geoarea contains a subset of the geographic locations that are less than all within the geoarea, and the segmentation is the expected user visit that meets the specified threshold. Steps and, which bring each geoarea with a number,
For each of the plurality of said geoareas, a step of ranking the geographic location of the geoarea, where each geographic location is scored with an eligibility value and said ranking is the eligibility of the geographic location. Steps, which are functions of sex values,
A step of selecting a geopoint from each of the geoareas as a location for presenting interactive features within the geomap interface of the remote geocaching data system, wherein the selected geopoint is a specific geographic location. A method comprising steps and corresponding to said particular geographic location having a higher rank than at least one other geographic location within the same geoarea. The steps to generate geopoint data by generating geopoints for each coordinate of said geographic location with a higher rank within each geoarea.
14. The method of claim 14, further comprising transmitting the geopoint data to the remote geocaching data system. 15. Method. A step of storing activity data for each of the geographic locations represented by the geocaching data, wherein the activity data is how often the one or more interactive features feature the remote geocaching data system. 16. The method of claim 16, further comprising a step indicating whether it is accessed by one or more terminal devices configured to communicate with. 17. The method of claim 17, wherein the eligibility value for each of the geographic locations is weighted in proportion to a value representing the amount of activity indicated by the activity data for the geographic location. Steps to determine an assessment schedule that specifies how often the multiple said geographic locations are ranked for the geoarea, and
17. The method of claim 17, further comprising segmenting the geographic map into alternative geoareas based on the evaluation schedule. The eligibility value for each geographic location is weighted based on the quality score data for the geographic location so that the quality score data for the geographic location communicates with the remote geocaching data system. 14. The method of claim 14, wherein the configured terminal device represents the probability of requesting data about said geographic location. Each geoarea contains less than a given number of geographic locations
15. The method of claim 14, wherein the segmentation step comprises segmentation resulting in each geoarea having an expected number of user visits by users of the remote geocaching data system that is less than the specified threshold. 15. The method of claim 14, wherein each geographic location is associated with a tier score for the geographic location, and the eligibility value for the geographic location is weighted in proportion to the tier score. A non-temporary computer-readable medium that stores instructions that can be executed by one or more processors configured to perform an operation, said operation.
Receiving geocaching data representing the geographic location specified by the remote geocaching data system from the remote geocaching data system.
Retaining data for each of the geographic locations represented by the geocaching data, the data specifying the number of expected user visits to the geographic location.
By segmenting a geographic map into geoareas based at least in part on the number of expected user visits to the geographic location, each geoarea is represented by the geocaching data. Each subset of the geographic locations for each geoarea contains a subset of the geographic locations that are less than all within the geoarea, and the segmentation is the expected user visit that meets the specified threshold. Bringing each geoarea with a number, and
For each of the plurality of said geoareas, ranking the geographic location of the geoarea, where each geographic location is scored with an eligibility value and said ranking is the eligibility of the geographic location. It is a function of sex value, and
Selecting a geopoint from each of the geoareas as a location for presenting interactive features within the geomap interface of the remote geocaching data system, wherein the selected geopoint is a particular geographic location. A non-temporary computer-readable medium that corresponds to the particular geographic location that has a higher rank than at least one other geographic location within the same geoarea.

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