CN113792227B - Method, system and medium for ranking application based on multidimensional intelligent screen - Google Patents
Method, system and medium for ranking application based on multidimensional intelligent screen Download PDFInfo
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Abstract
The invention discloses a method, a system and a medium for applying ranking based on a multi-dimensional intelligent screen, wherein the method comprises the following steps: setting a plurality of first data information and data mapping conversion strategies to be applied in ranking; acquiring the first data information, the second data information and the third data information of a plurality of applications to be ranked, and constructing ranking data of each application to be ranked according to the data mapping conversion strategy, the first data information, the second data information and the third data information; executing application ranking operation on a plurality of applications to be ranked according to the ranking data; by means of the method, the ranking of the intelligent screen application can be integrally optimized through multi-dimensional comparison under the condition that the original intelligent screen ranking algorithm codes are not changed, storage space is saved, accuracy of ranking of the intelligent screen application in a ecological application system is guaranteed, and operation efficiency of the intelligent screen application ranking algorithm is improved.
Description
Technical Field
The invention relates to the technical field of application ranking, in particular to a method, a system and a medium for application ranking based on a multi-dimensional intelligent screen.
Background
With the rise of intelligent terminals, more applications are installed on the intelligent terminals, and more applications are selected by users, so that how to select the applications becomes a difficult problem. Aiming at the difficult problem, the ranking of the application is designed in each application mall, when a user searches for an application of a certain class, the ranking is generated in the application mall according to various data of each application, and the user can select according to the ranking and combining with the actual application of the user.
Existing algorithms for applying ranking generally calculate the ranking by means of a zsort data structure of redis; when zsort score is the same, two cache keys are set, key1 stores the number and priority information of the application, key2 stores the number, the application downloading amount and the application time of the application, when the application is ranked, zsort sets are all traversed, when score is the same, key2 data are traversed to obtain the downloading amount and the time information of the application, and secondary ranking is performed.
However, the ranking algorithm causes too high data overhead and wastes larger storage space, and meanwhile, the front-end response speed is reduced, and the speed advantage of caching the database is lost.
Disclosure of Invention
The invention mainly solves the problems that the data overhead of the existing application ranking algorithm is too large, the storage space is wasted and the response speed is slow.
In order to solve the problems, the invention adopts a technical scheme that: there is provided a method for multi-dimensional intelligent screen application ranking, comprising the steps of:
Initializing: setting first data information of a plurality of applications to be ranked; constructing a data mapping conversion strategy according to a plurality of first data information;
Building ranking data: acquiring the first data information, the second data information and the third data information of a plurality of applications to be ranked, and constructing ranking data of each application to be ranked according to the data mapping conversion strategy, the first data information, the second data information and the third data information;
application ranking: and executing application ranking operation on a plurality of applications to be ranked according to the ranking data.
Further, the step of constructing ranking data further comprises:
Acquiring first data: acquiring the first data information of a plurality of applications to be ranked, and performing mapping operation on the first data information according to the data mapping conversion strategy to obtain a plurality of first conversion data;
Acquiring second data: acquiring the second data information of a plurality of applications to be ranked, and executing second data conversion operation on the second data information to obtain a plurality of second conversion data;
and acquiring third data: acquiring the third data information of a plurality of applications to be ranked, and executing third data conversion operation on the third data information to obtain a plurality of third conversion data;
Obtaining ranking data: and performing data splicing operation on the first mapping data, the second conversion data and the third conversion data to obtain ranking data.
Further, the step of acquiring the first data further includes:
Acquiring the first data information of a plurality of applications to be ranked, and acquiring a plurality of first data information; and carrying out data mapping conversion on each piece of first data information according to a data mapping conversion strategy to obtain the first conversion data of each application to be ranked.
Further, the step of acquiring the second data further includes:
acquiring the second data information of a plurality of applications to be ranked, and acquiring a plurality of second data information;
And acquiring first attribute information of a plurality of pieces of second data information, and respectively executing second data conversion operation on the plurality of pieces of first attribute information to obtain second conversion data of each application to be ranked.
Further, the step of performing the second data conversion operation on the plurality of pieces of the first attribute information, respectively, further includes:
performing size comparison operation on the plurality of first attribute information to obtain maximum first attribute information; and executing data bit filling operation on a plurality of other first attribute information according to the maximum first attribute information.
Further, the step of acquiring third data further includes:
acquiring the third data information of a plurality of applications to be ranked, and acquiring a plurality of third data information; and carrying out format conversion on the plurality of third data information to obtain the third conversion data of each application to be ranked.
Further, the step of obtaining ranking data further comprises:
Acquiring the first conversion data, the second conversion data and the third conversion data of each application to be ranked, and splicing the second conversion data at the tail end of the first conversion data to obtain temporary ranking data; and splicing the third conversion data at the tail end of the temporary ranking data to obtain the ranking data of each application to be ranked.
Further, the step of applying the ranking further comprises:
acquiring the ranking data of a plurality of applications to be ranked, and constructing a ranking data set according to the applications to be ranked and the ranking data; a ranking operation is performed on the set of ranking data.
A system for multidimensional intelligent screen application ranking, comprising: the system comprises an initialization module, a ranking data construction module and an application ranking module;
The initialization module is used for setting first data information of a plurality of applications to be ranked; constructing a data mapping conversion strategy according to a plurality of first data information;
The ranking data constructing module is used for acquiring the first data information, the second data information and the third data information of a plurality of applications to be ranked and constructing ranking data of each application to be ranked according to the data mapping conversion strategy, the first data information, the second data information and the third data information;
The application ranking module is used for executing application ranking operation on a plurality of applications to be ranked according to the ranking data;
the ranking data constructing module comprises a first data unit, a second data unit, a third data unit and a ranking data unit;
the first data obtaining unit is used for obtaining the first data information of a plurality of applications to be ranked, and mapping operation is performed on the first data information according to the data mapping conversion strategy to obtain a plurality of first conversion data;
The second data obtaining unit is used for obtaining second data information of a plurality of applications to be ranked, and performing second data conversion operation on the second data information to obtain a plurality of second conversion data;
The third data obtaining unit is used for obtaining a plurality of third data information of the application to be ranked, and executing third data conversion operation on the third data information to obtain a plurality of third conversion data;
The ranking data obtaining unit is used for performing data splicing operation on the first mapping data, the second conversion data and the third conversion data to obtain ranking data.
The invention also provides a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method for multi-dimensional intelligent screen application ranking.
The beneficial effects of the invention are as follows:
1. The method for ranking the intelligent screen application based on the multi-dimension can realize the integral optimization of the ranking algorithm of the intelligent screen application under the condition of not changing the original code, save the storage space and improve the operation efficiency of the ranking algorithm of the intelligent screen application;
2. The system based on the multi-dimensional intelligent screen application ranking can realize the ranking calculation of the intelligent screen application through the multi-dimension, ensure the accuracy of the intelligent screen application ranking and improve the experience of users;
3. The medium based on the multi-dimensional intelligent screen application ranking can solve the problems of long time consumption and inaccurate ranking of the intelligent screen application ranking under the condition of the same downloading amount, and the accuracy of the intelligent screen application ranking is improved by introducing the multi-dimensional intelligent screen application ranking.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for multi-dimensional intelligent screen application ranking based on embodiment 1 of the present invention;
FIG. 2 is a flowchart of the steps of constructing ranking data for a method based on multi-dimensional intelligent screen application ranking according to embodiment 1 of the present invention;
FIG. 3 is a schematic diagram of a system for multi-dimensional intelligent screen application ranking based on embodiment 2 of the present invention;
FIG. 4 is a schematic diagram of a system for constructing ranking data module based on multi-dimensional intelligent screen application ranking according to embodiment 2 of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made apparent and fully in view of the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, unless explicitly specified and limited otherwise, terms such as "application to be ranked", "first data information", "data mapping conversion policy", "second data information", "third data information", "ranking data", "application ranking operation", "mapping operation", "first conversion data", "second data conversion operation", "second conversion data", "third data conversion operation", "third conversion data", "data stitching operation", "first attribute information", "maximum first attribute information", "data bit supplementing operation", "format conversion", "temporary ranking data", "ranking data set", "initialization module", "build ranking data module", "application ranking module", "acquire first data unit", "acquire second data unit", "acquire third data unit", "acquire ranking data unit", "priority map data", "application download amount", "bit supplementing amount data", "time", "formatting", "time data of the time", "end", "intelligent screen ecology application system", "front end", "ranking display" and the like are to be interpreted in a broad sense. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first", "a second", and "a third" may explicitly or implicitly include at least one such feature.
Example 1
The embodiment of the invention provides a method for applying ranking based on a multi-dimensional intelligent screen, referring to fig. 1 and 2, comprising the following steps:
s100, initializing:
acquiring all applications to be ranked in the intelligent screen ecological application system, and setting first data information, namely priority, for all applications; setting a corresponding data mapping conversion strategy according to the priority.
For a clearer explanation of the present invention, it is exemplified herein that 10 applications requiring ranking in the current smart screen ecological application system are assumed, and the names are application one, application two, application three, application four, application five, application six, application seven, application eight, application nine, application ten, respectively; then the 10 applications need to be set with priority according to actual demands, the priority of application one is set to 8, the priority of application two is set to 3, the priority of application three is set to 9, the priority of application four is set to 7, the priority of application five is set to 1, the priority of application six is set to 2, the priority of application seven is set to 4, the priority of application eight is set to 6, the priority of application nine is set to 0, and the priority of application ten is set to 5; setting the data mapping conversion strategy to be 9 corresponding to the priority of 0, 8 corresponding to the priority of 1, 7 … … corresponding to the priority of 2 and so on, wherein the mapping value corresponding to the priority of 9 is 0.
S200, constructing ranking data:
s201, acquiring first data:
Acquiring first data information, namely priorities, of a plurality of applications to be ranked, and acquiring a plurality of priorities; and converting the priority of each application with ranking according to the data mapping conversion strategy to obtain first conversion data, namely priority mapping data, of each application to be ranked.
For more clear explanation of the present invention, continuing the illustration in the step of S100 initialization, the priority of application one is obtained as 8, and the priority of application one is converted according to the data mapping conversion policy, so as to obtain the priority mapping data of application one as 1; the priority of the application II is obtained to be 3, the priority of the application II is converted according to the data mapping conversion strategy, the priority mapping data of the application II is obtained to be 6 … … and the like, and the respective priority mapping data of ten applications can be obtained in sequence.
S202, acquiring second data:
Acquiring second data information of a plurality of applications to be ranked, namely application downloading amounts, and obtaining a plurality of application downloading amounts; acquiring first attribute information of application downloading amount of each application to be ranked, namely application downloading amount digits, and obtaining a plurality of application downloading amount digits;
traversing a plurality of application downloading amount digits to obtain the maximum application downloading amount digits, supplementing other application downloading amounts according to the value of the maximum application downloading amount digits, supplementing other application downloading amounts with the digits, wherein the digits of the obtained numerical values are the same as the maximum application downloading amount digits, and the supplementary digits of each application downloading amount have the same value and are all supplementary digits at the left side of the application downloading amount; and completing the bit filling, and obtaining second conversion data and bit filling downloading amount data of each application to be ranked.
For a clearer explanation of the present invention, the example in the step of acquiring the first data is described here with S201, assuming that the first downloading amount is 14932510, assuming that the second downloading amount is 8532412, assuming that the third downloading amount is 87138, assuming that the fourth downloading amount is 12647, assuming that the fifth downloading amount is 23654, assuming that the sixth downloading amount is 85401, assuming that the seventh downloading amount is 42156, assuming that the eighth downloading amount is 9513, assuming that the ninth downloading amount is 22189, assuming that the tenth downloading amount is 1635, the number of bits of the ten downloading amounts is acquired, traversing the ten downloading amount bit numbers respectively is larger, and the number of bits of the largest downloading amount is 8, that is, the number of bits of the downloading amount of the first downloading amount is the largest, then the number of the downloading amount bits of the second downloading amount to the tenth downloading amount is 12647, the value of the supplementing bit is selected here to be 0, the downloading amount of the first downloading amount of the data is 14932510, the number of the downloading amount of bits of the second downloading amount is 08532412, the number of the downloading amount of the third downloading amount of the fourth downloading amount is 4225, and the fourth downloading amount of the data is 4225.
S203, acquiring third data:
Acquiring third data information of a plurality of applications to be ranked, namely, the time to put on shelf, and obtaining a plurality of time to put on shelf; after formatting the plurality of time-to-shelf, third conversion data of each application to be ranked, namely time-to-shelf data, can be obtained.
For a clearer explanation of the present invention, the step S202 of acquiring the second data is continued to be exemplified here, in which the first set of the application is acquired for 5 months and 6 days in 2020, the second set of the application is acquired for 4 months and 7 days in 2020, the third set of the application is acquired for 4 months and 6 days in 2021, the fourth set of the application is acquired for 3 months and 9 days in 2020, the fifth set of the application is acquired for 12 months and 10 days in 2020, the sixth set of the application is acquired for 8 months and 8 days in 2020, the seventh set of the application is acquired for 2021 month and 4 days in 2021, the eighth set of the application is acquired for 2 months and 2 days in 2021, the ninth set of the application is acquired for 4 months and 9 days in 2021, and the tenth set of the application is acquired for 6 months and 6 days in 2021; formatting the time of the overhead of ten applications can obtain the time data of the overhead of application one of 20200506, the time data of the overhead of application two of 20200407, the time data of the overhead of application three of 20210406, the time data of the overhead of application four of 20200309, the time data of the overhead of application five of 20201210, the time data of the overhead of application six of 20200808, the time data of the overhead of application seven of 20210104, the time data of the overhead of application eight of 20210202, the time data of the overhead of application nine of 20210409, and the time data of the overhead of application ten of 20210606.
S204, acquiring ranking data:
Acquiring priority mapping data, bit filling downloading amount data and time-to-put data of each application to be ranked, and splicing the bit filling downloading amount data at the tail end of the priority mapping data to obtain temporary ranking data; and splicing the time-to-live data at the tail end of the temporary ranking data to obtain the ranking data of the application to be ranked.
For a clearer explanation of the present invention, the step S203 of obtaining the third data is continued to illustrate the example, where the priority mapping data of application one is 1, the bit-complementary downloading amount data of application one is 14932510, and the time-to-live data of application one is 20200506, so that the ranking data of application one can be obtained as 11493251020200506, and similarly, the ranking data of application two can be obtained as 60853241220200407 … …, and so on, the ranking data of each of ten applications to be ranked can be obtained.
S300, ranking is applied:
And acquiring ranking data of a plurality of applications to be ranked, constructing a ranking data set according to the applications to be ranked and the ranking data thereof, and sequencing the ranking data set, namely comparing the size of the ranking data of each application to be ranked, so that the ranking order of the applications to be ranked can be obtained, and pushing the data to the front end of the intelligent screen ecological application system for application ranking display.
For a clearer explanation of the present invention, the step of obtaining ranking data in S204 is exemplified herein, wherein the ranking data sets are { ("application one", "11493251020200506"), ("application two", "60853241220200407") … … ("application ten", "40000163520210606") }, and ranking orders of ten applications can be obtained by comparing the sizes of the ranking data values according to ranking calculation performed on the ranking data sets.
It should be noted that the foregoing examples are only for explaining the implementation of the present invention, and are not intended to limit the scope of the present invention.
Example 2
The embodiment of the invention also provides a system for applying ranking based on the multi-dimensional intelligent screen, referring to fig. 3 and 4, comprising: the system comprises an initialization module, a ranking data construction module and an application ranking module;
An initialization module:
The initialization module is used for setting first data information of a plurality of applications to be ranked; constructing a data mapping conversion strategy according to a plurality of first data information;
specifically, an initialization module acquires all applications to be ranked in an intelligent screen ecological application system, and sets first data information, namely priority, for all applications; setting a corresponding data mapping conversion strategy according to the priority.
For a clearer explanation of the present invention, it is exemplified herein that 10 applications requiring ranking in the current smart screen ecological application system are assumed, and the names are application one, application two, application three, application four, application five, application six, application seven, application eight, application nine, application ten, respectively; then the 10 applications need to be set with priority according to actual demands, the priority of application one is set to 8, the priority of application two is set to 3, the priority of application three is set to 9, the priority of application four is set to 7, the priority of application five is set to 1, the priority of application six is set to 2, the priority of application seven is set to 4, the priority of application eight is set to 6, the priority of application nine is set to 0, and the priority of application ten is set to 5; setting the data mapping conversion strategy to be 9 corresponding to the priority of 0, 8 corresponding to the priority of 1, 7 … … corresponding to the priority of 2 and so on, wherein the mapping value corresponding to the priority of 9 is 0.
And (3) constructing a ranking data module:
The ranking data constructing module is used for acquiring first data information, second data information and third data information of a plurality of applications to be ranked and constructing ranking data of each application to be ranked according to a data mapping conversion strategy, the first data information, the second data information and the third data information; the ranking data module is constructed and comprises a first data unit, a second data unit, a third data unit and a ranking data unit;
Acquiring a first data unit:
The method comprises the steps of obtaining a first data unit, wherein the first data unit is used for obtaining the first data information of a plurality of applications to be ranked, and performing mapping operation on the first data information according to the data mapping conversion strategy to obtain a plurality of first conversion data;
Specifically, acquiring a first data unit to acquire first data information, namely priorities, of a plurality of applications to be ranked, and acquiring a plurality of priorities; and converting the priority of each application with ranking according to the data mapping conversion strategy to obtain first conversion data, namely priority mapping data, of each application to be ranked.
For more clear explanation of the present invention, continuing the illustration in the initialization module here, the priority of application one is obtained as 8, and the priority of application one is converted according to the data mapping conversion policy, so as to obtain the priority mapping data of application one as 1; the priority of the application II is obtained to be 3, the priority of the application II is converted according to the data mapping conversion strategy, the priority mapping data of the application II is obtained to be 6 … … and the like, and the respective priority mapping data of ten applications can be obtained in sequence.
Acquiring a second data unit:
The method comprises the steps of obtaining second data units, which are used for obtaining second data information of a plurality of applications to be ranked, and executing second data conversion operation on the second data information to obtain a plurality of second conversion data;
specifically, acquiring a second data unit to acquire second data information of a plurality of applications to be ranked, namely application downloading amounts, so as to obtain a plurality of application downloading amounts; acquiring first attribute information of application downloading amount of each application to be ranked, namely application downloading amount digits, and obtaining a plurality of application downloading amount digits;
traversing a plurality of application downloading amount digits to obtain the maximum application downloading amount digits, supplementing other application downloading amounts according to the value of the maximum application downloading amount digits, supplementing other application downloading amounts with the digits, wherein the digits of the obtained numerical values are the same as the maximum application downloading amount digits, and the supplementary digits of each application downloading amount have the same value and are all supplementary digits at the left side of the application downloading amount; and completing the bit filling, and obtaining second conversion data and bit filling downloading amount data of each application to be ranked.
For a clearer explanation of the present invention, it is assumed that the first data unit is further obtained by taking the example of 14932510 for the first download, 8532412 for the second download, 87138 for the third download, 12647 for the fourth download, 23654 for the fifth download, 85401 for the sixth download, 42156 for the seventh download, 9513 for the eighth download, 22189 for the ninth download, 1635 for the tenth download, and a number of bits of the ten downloads of the ten applications, and traversing the ten download bit numbers of 8 for the maximum download, that is, the number of bits of the download for the first application is the maximum, and the number of bits of the download for the second to the tenth needs to be complemented, where 0 is selected as the complement bit value, the complement data for the first download is 14932510, the bit download data for the second application is 08532412, the download data for the third download is the fourth download is the 4225, and so on.
Acquiring a third data unit:
the method comprises the steps of obtaining a third data unit, which is used for obtaining third data information of a plurality of applications to be ranked, and executing third data conversion operation on the third data information to obtain a plurality of third conversion data;
Specifically, acquiring a third data unit to acquire third data information of a plurality of applications to be ranked, namely, the time to put on shelf, and acquiring a plurality of time to put on shelf; after formatting the plurality of time-to-shelf, third conversion data of each application to be ranked, namely time-to-shelf data, can be obtained.
For a clearer explanation of the present invention, the examples in the second data unit are continued here, the first application's overhead time is 2020, 5, 6, the second application's overhead time is 2020, 4, 7, 2021, 4, 6, four application's overhead time is 2020, 3, 9, five application's overhead time is 2020, 12, 10, six application's overhead time is 2020, 8, 2021, 1, 4, 2021, 2, 2021, 4, 9, and 2021, 6. Formatting the time of the overhead of ten applications can obtain the time data of the overhead of application one of 20200506, the time data of the overhead of application two of 20200407, the time data of the overhead of application three of 20210406, the time data of the overhead of application four of 20200309, the time data of the overhead of application five of 20201210, the time data of the overhead of application six of 20200808, the time data of the overhead of application seven of 20210104, the time data of the overhead of application eight of 20210202, the time data of the overhead of application nine of 20210409, and the time data of the overhead of application ten of 20210606.
Obtaining a ranking data unit:
the method comprises the steps that a ranking data unit is obtained and used for performing data splicing operation on a plurality of first mapping data, a plurality of second conversion data and a plurality of third conversion data to obtain a plurality of ranking data;
Specifically, a ranking data obtaining unit obtains priority mapping data, bit filling downloading amount data and time-to-put data of each application to be ranked, and splices the bit filling downloading amount data at the tail end of the priority mapping data to obtain temporary ranking data; and splicing the time-to-live data at the tail end of the temporary ranking data to obtain the ranking data of the application to be ranked.
For a clearer explanation of the present invention, the example of obtaining the third data unit is continued to be described herein, the priority mapping data of application one is 1, the bit-filling downloading amount data of application one is 14932510, the time-to-put data of application one is 20200506, so that the ranking data of application one can be obtained as 11493251020200506, the ranking data of application two can be obtained as 60853241220200407 … …, and the like, and the ranking data of each of ten applications to be ranked can be obtained.
An application ranking module:
the application ranking module is used for executing application ranking operation on a plurality of applications to be ranked according to ranking data;
The application ranking module acquires ranking data of a plurality of applications to be ranked, builds a ranking data set according to the applications to be ranked and the ranking data thereof, and ranks the ranking data set, namely compares the size of the ranking data of each application to be ranked, so that the ranking order of the applications to be ranked can be obtained, and the data is pushed to the front end of the intelligent screen ecological application system for application ranking display.
For a clearer explanation of the present invention, the examples of obtaining ranking data units are continued to illustrate herein, the ranking data sets are { ("application one", "11493251020200506"), ("application two", "60853241220200407") … … ("application ten", "40000163520210606") }, and ranking orders of ten applications can be obtained by comparing the sizes according to the values of the ranking data when ranking calculation is performed on the ranking data sets.
It should be noted that the foregoing examples are only for explaining the implementation of the present invention, and are not intended to limit the scope of the present invention.
Example 3
This embodiment 3 has a computer-readable storage medium for storing computer software instructions for implementing the method for multi-dimensional smart screen application ranking described in embodiment 1, which contains a program set for the method for multi-dimensional smart screen application ranking; specifically, the executable program may be built in the system based on multi-dimensional smart screen application ranking described in embodiment 2, so that the system based on multi-dimensional smart screen application ranking may implement the method based on multi-dimensional smart screen application ranking described in embodiment 1 by executing the built-in executable program.
The foregoing embodiment of the present invention has been disclosed with reference to the number of embodiments for the purpose of description only, and does not represent the advantages or disadvantages of the embodiments.
It will be appreciated by those of ordinary skill in the art that all or part of the steps of implementing the above embodiments may be implemented by hardware, or a program implemented by a program to instruct related hardware may be stored in a computer readable storage medium, where the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The foregoing description is only illustrative of the present invention and is not intended to limit the scope of the invention, and all equivalent structures or equivalent processes or direct or indirect application in other related technical fields are included in the scope of the present invention.
Claims (6)
1. A method for multi-dimensional intelligent screen application ranking, comprising the steps of:
Initializing: setting first data information of a plurality of applications to be ranked; constructing a data mapping conversion strategy according to a plurality of first data information;
Building ranking data: acquiring the first data information, the second data information and the third data information of a plurality of applications to be ranked, and constructing ranking data of each application to be ranked according to the data mapping conversion strategy, the first data information, the second data information and the third data information;
application ranking: executing application ranking operation on a plurality of applications to be ranked according to the ranking data;
the step of constructing ranking data further comprises:
Acquiring first data: acquiring the first data information of a plurality of applications to be ranked, and performing mapping operation on the first data information according to the data mapping conversion strategy to obtain a plurality of first conversion data;
Acquiring second data: acquiring the second data information of a plurality of applications to be ranked, and executing second data conversion operation on the second data information to obtain a plurality of second conversion data;
and acquiring third data: acquiring the third data information of a plurality of applications to be ranked, and executing third data conversion operation on the third data information to obtain a plurality of third conversion data;
obtaining ranking data: performing data splicing operation on the first conversion data, the second conversion data and the third conversion data to obtain ranking data;
the step of acquiring the first data further comprises:
Acquiring the first data information of a plurality of applications to be ranked, and acquiring a plurality of first data information; performing data mapping conversion on each piece of first data information according to a data mapping conversion strategy to obtain the first conversion data of each application to be ranked;
The step of acquiring second data further comprises:
acquiring the second data information of a plurality of applications to be ranked, and acquiring a plurality of second data information;
Acquiring first attribute information of a plurality of pieces of second data information, and respectively executing second data conversion operation on the plurality of pieces of first attribute information to obtain second conversion data of each application to be ranked;
The step of performing the second data conversion operation on the plurality of pieces of the first attribute information, respectively, further includes:
performing size comparison operation on the plurality of first attribute information to obtain maximum first attribute information; and executing data bit filling operation on a plurality of other first attribute information according to the maximum first attribute information.
2. A method of multi-dimensional intelligent screen application ranking according to claim 1, wherein: the step of acquiring third data further comprises:
acquiring the third data information of a plurality of applications to be ranked, and acquiring a plurality of third data information; and carrying out format conversion on the plurality of third data information to obtain the third conversion data of each application to be ranked.
3. A method of multi-dimensional intelligent screen application ranking according to claim 1, wherein: the step of obtaining ranking data further comprises:
Acquiring the first conversion data, the second conversion data and the third conversion data of each application to be ranked, and splicing the second conversion data at the tail end of the first conversion data to obtain temporary ranking data; and splicing the third conversion data at the tail end of the temporary ranking data to obtain the ranking data of each application to be ranked.
4. A method of multi-dimensional intelligent screen application ranking according to claim 1, wherein: the step of applying a ranking further comprises:
acquiring the ranking data of a plurality of applications to be ranked, and constructing a ranking data set according to the applications to be ranked and the ranking data; a ranking operation is performed on the set of ranking data.
5. A system for multi-dimensional intelligent screen application ranking, employing a multi-dimensional intelligent screen application ranking based method of claim 1, the system comprising: the system comprises an initialization module, a ranking data construction module and an application ranking module;
The initialization module is used for setting first data information of a plurality of applications to be ranked; constructing a data mapping conversion strategy according to a plurality of first data information;
The ranking data constructing module is used for acquiring the first data information, the second data information and the third data information of a plurality of applications to be ranked and constructing ranking data of each application to be ranked according to the data mapping conversion strategy, the first data information, the second data information and the third data information;
The application ranking module is used for executing application ranking operation on a plurality of applications to be ranked according to the ranking data;
the ranking data constructing module comprises a first data unit, a second data unit, a third data unit and a ranking data unit;
the first data obtaining unit is used for obtaining the first data information of a plurality of applications to be ranked, and mapping operation is performed on the first data information according to the data mapping conversion strategy to obtain a plurality of first conversion data;
The second data obtaining unit is used for obtaining second data information of a plurality of applications to be ranked, and performing second data conversion operation on the second data information to obtain a plurality of second conversion data;
The third data obtaining unit is used for obtaining a plurality of third data information of the application to be ranked, and executing third data conversion operation on the third data information to obtain a plurality of third conversion data;
The ranking data obtaining unit is used for performing data splicing operation on the first conversion data, the second conversion data and the third conversion data to obtain ranking data.
6. A computer readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the method steps of any one of claims 1-4 for multi-dimensional intelligent screen based application ranking.
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| CN105912599A (en) * | 2016-03-31 | 2016-08-31 | 维沃移动通信有限公司 | Ranking method and terminal of terminal application programs |
| CN108769756A (en) * | 2018-05-02 | 2018-11-06 | 武汉斗鱼网络科技有限公司 | With ranking main broadcaster sort method and system, server and storage medium again |
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| CN105912599A (en) * | 2016-03-31 | 2016-08-31 | 维沃移动通信有限公司 | Ranking method and terminal of terminal application programs |
| CN108769756A (en) * | 2018-05-02 | 2018-11-06 | 武汉斗鱼网络科技有限公司 | With ranking main broadcaster sort method and system, server and storage medium again |
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