CN109657063A - A kind of processing method and storage medium of magnanimity environment-protection artificial reported event data - Google Patents
A kind of processing method and storage medium of magnanimity environment-protection artificial reported event data Download PDFInfo
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Abstract
The present invention relates to the processing methods and storage medium of a kind of magnanimity environment-protection artificial reported event data, it the described method comprises the following steps: extracting history and report the characteristic value of event data and report event data that label is set history, be trained to obtain event category model according to the label of the characteristic value of extraction and setting；When getting new reported event data, event keyword is distributed to new reported event data, and extract the characteristic value of new reported event data；According to the event keyword of distribution and the characteristic value of extraction, merging data is formed after new reported event data are sorted out and merged by event category model；Merging data is sent to according to classification and accepts end.The data in environmentally friendly event manually reported by automatic identification, such as event content, address, time information, classifying intelligently integrate similar case and reduce the redundancy that system accepts event.
Description
Technical field
The present invention designs environment protection digital and reports technical field, is specifically designed a kind of magnanimity environment-protection artificial reported event data
Processing method and storage medium.
Background technique
With the propulsion of current national environmental protection grid supervisory system is implemented, the environmentally friendly public play an active part in and mobile terminal
Popularization and application, the environmentally friendly event information manually reported becomes more further, and the environmentally friendly event person of accepting task is further heavy.Wherein
The environmentally friendly event information manually reported includes 12369 environmentally friendly hotline of complaint information, the related complaint of mayor's hot line environmental protection, masses' wechat
It reports and environmentally friendly grid person reports environmentally friendly event etc..
The current existing informatization management method for reporting environmentally friendly event to accept and system mainly by by above call time, on
Channel, reported event type is reported to carry out Classification Management.But such management method and system there are same environmentally friendly event by all kinds of means on
Report reports repetition situation with the more people of channel, for example, same environmental pollution Event origin reported in grid person, masses' wechat,
12369 complaints etc. are multiple to report channel, and there is also same people to report situation multiple periods, while because of artificial reported event content
The not first-class reason of describing mode causes to produce larger redundancy environmental protection reported event information in management system.When magnanimity is artificial
It reports environmentally friendly quantity to accept in the Information Management System of which, will greatly reduce the environmentally friendly event person's of accepting of the system
Event accepts efficiency.Assigning for reported event needs to cooperate with multiple departments to go to handle simultaneously, this requires the environmentally friendly event person of accepting right
Process flow and each department's function are very familiar, otherwise be easy to cause event to accept overstocked.
Summary of the invention
For this reason, it may be necessary to provide the processing method and storage medium of a kind of magnanimity environment-protection artificial reported event data, solve existing
Have environmentally friendly event accept informatization management method and system can not effectively distinguish it is in fact duplicate manually report environmentally friendly event, produce
The problem of having given birth to larger amount of redundancy environmental protection reported event information.
To achieve the above object, a kind of processing method of magnanimity environment-protection artificial reported event data is inventor provided, is wrapped
Include following steps:
It extracts history to report the characteristic value of event data and report event data that label is arranged history, according to the spy of extraction
Value indicative and the label of setting are trained to obtain event category model；
When getting new reported event data, event keyword is distributed to new reported event data, and extract new
Reported event data characteristic value；
According to the event keyword of distribution and the characteristic value of extraction, by event category model to new reported event data
Sorted out and forms merging data after being merged；
Merging data is sent to according to classification and accepts end.
It advanced optimizes, it is described " to extract history to report the characteristic value of event data and report event data to be arranged history
Label is trained to obtain event category model according to the label of the characteristic value of extraction and setting " specifically includes the following steps:
The exclusive dictionary of reported event is established according to event keyword；
It reports event data as sample using history, reports the content of text of event data to history using full-text search engine
It carries out automatic word segmentation and matches the corresponding exclusive dictionary of reported event, establish history and report reflecting for event data and event keyword
It penetrates；
The characteristic value for extracting history reported event, reports the event keyword of event data to be converted to characteristic value history
Mathematic vector space with initialization weighted value, is classified automatically using k- k-nearest neighbor, forms event category model.
It advanced optimizes, further comprising the steps of after described " being classified automatically using k- k-nearest neighbor ":
The duplicate removal result for reporting event data to classify using history automatically adjusts band initialization weighted value as score basis
It is excellent, disaggregated model is generated based on the weighted value after tuning.
Advanced optimize, the characteristic value include the GPS longitude and latitude of reported event, report channel, upper journalist, on give the correct time
Between；The event keyword includes event type, event argument, event object.
Advanced optimize, described " merging data is sent to according to classification and accepts end " specifically includes the following steps:
Merging data is associated with similar history by event keyword and reports event data and preset rules；
Acquisition association is corresponding to accept information, and the information that accepts includes accepting measure, accepting process and cooperation department；
By merging data and accepts information and be sent to and accept end.
Inventor additionally provides another technical solution: a kind of storage medium, is stored with computer in the storage medium
Program, which is characterized in that the computer program executes following steps when being run by processor:
It extracts history to report the characteristic value of event data and report event data that label is arranged history, according to the spy of extraction
Value indicative and the label of setting are trained to obtain event category model；
When getting new reported event data, event keyword is distributed to new reported event data, and extract new
Reported event data characteristic value；
According to the event keyword of distribution and the characteristic value of extraction, by event category model to new reported event data
Sorted out and forms merging data after being merged；
Merging data is sent to according to classification and accepts end.
It advanced optimizes, the processor executes the step and " extracts history and report the characteristic value of event data and to going through
Label is arranged in history reported event data；It is trained to obtain event category model according to the label of the characteristic value of extraction and setting "
When, specifically execute following steps:
The exclusive dictionary of reported event is established according to event keyword；
It reports event data as sample using history, reports the content of text of event data to history using full-text search engine
It carries out automatic word segmentation and matches the corresponding exclusive dictionary of reported event, establish history and report reflecting for event data and event keyword
It penetrates；
The characteristic value for extracting history reported event, reports the event keyword of event data to be converted to characteristic value history
Mathematic vector space with initialization weighted value, is classified automatically using k- k-nearest neighbor, forms event category model.
It advanced optimizes, the processor is gone back after executing the step " being classified automatically using k- k-nearest neighbor "
Execute following steps:
The duplicate removal result for reporting event data to classify using history automatically adjusts band initialization weighted value as score basis
It is excellent, disaggregated model is generated based on the weighted value after tuning.
Advanced optimize, the characteristic value include the GPS longitude and latitude of reported event, report channel, upper journalist, on give the correct time
Between；The event keyword includes event type, event argument, event object.
It advanced optimizes, when the processor executes step " be sent to merging data according to classification and accept end ",
It is specific to execute following steps:
Merging data is associated with similar history by event keyword and reports event data and preset rules；
Acquisition association is corresponding to accept information, and the information that accepts includes accepting measure, accepting process and cooperation department；
By merging data and accepts information and be sent to and accept end.
It is different from the prior art, above-mentioned technical proposal, by reporting event data to obtain as sample training according to history
Then event category model extracts event keyword and characteristic value etc. in environmentalist's reported event data, according to event point
Class model automatic clustering merges to form merging data, is then sent to and accepts end, the environmentally friendly thing manually reported by automatic identification
Data in part, such as event content, address, time information, classifying intelligently integrate similar case reduction system and accept event
Redundancy.
Detailed description of the invention
Fig. 1 is a kind of process signal of the processing method of magnanimity environment-protection artificial reported event data described in specific embodiment
Figure；
Fig. 2 is a kind of structural schematic diagram of storage medium described in specific embodiment.
Specific embodiment
Technology contents, construction feature, the objects and the effects for detailed description technical solution, below in conjunction with specific reality
It applies example and attached drawing is cooperated to be explained in detail.
Referring to Fig. 1, the processing method of magnanimity environment-protection artificial reported event data described in the present embodiment, including following step
It is rapid:
Step S110: it extracts history and reports the characteristic value of event data and report event data that label, root are set history
It is trained to obtain event category model according to the characteristic value of extraction and the label of setting；By using history reported event as sample
This, carries out establishing event category model, carry out for being identified to environmentalist by the event that manual type reports,
In, specifically establishing event category model, specific step is as follows:
The exclusive dictionary of reported event is established according to event keyword；
It reports event data as sample using history, reports the content of text of event data to history using full-text search engine
It carries out automatic word segmentation and matches the corresponding exclusive dictionary of reported event, establish history and report reflecting for event data and event keyword
It penetrates；
The characteristic value for extracting history reported event, reports the event keyword of event data to be converted to characteristic value history
Mathematic vector space with initialization weighted value, is classified automatically using k- k-nearest neighbor, forms event category model.
Wherein, event keyword includes event type, event argument, event object.
Mapping between event data and event keyword is reported by establishing history, history reported event is configured
Corresponding label such as establishes the exclusive dictionary A of reported event according to event keyword a, then obtains history and reports event data, with
It is sample that history, which reports event data, reports the content of text of event data to the history as sample using full-text search engine
The exclusive dictionary of the corresponding reported event of Auto-matching is carried out, i.e., whether retrieved to the content of text of sample includes to report thing
Keyword corresponding to the exclusive dictionary of part such as retrieves when including keyword a, is then matched in dictionary A, establishes history and report
Mapping between event data and event keyword.
And in order to establish optimal classification model, after described " being classified automatically using k- k-nearest neighbor " further include with
Lower step: the duplicate removal result for reporting event data to classify using history automatically adjusts band initialization weighted value as score basis
It is excellent, disaggregated model is generated based on the weighted value after tuning.By the duplicate removal result that reports event data to classify using history as commenting
Point foundation carries out tuning to band initialization weighted value so that weighted value can achieve it is optimal, and then based on the weighted value after tuning
Optimal disaggregated model can be generated, keep the classification to new reported event data more accurate.
Step S120: when getting new reported event data, distributing event keyword to new reported event data,
And extract the characteristic value of new reported event data；Characteristic value include the GPS longitude and latitude of reported event, report channel, upper journalist,
On call time.
Step S130: according to the event keyword of distribution and the characteristic value of extraction, by event category model to new upper
Report event data is sorted out and forms merging data after being merged；
Step S140: merging data is sent to according to classification and accepts end.
And when environmentalist reports new reported event data, event is allocated to new reported event data automatically
Then keyword extracts the characteristic value etc. in environmentalist's reported event data, then according to event category model automatic clustering
Merging forms merging data, is then sent to and accepts end, the data in environmentally friendly event manually reported by automatic identification, such as thing
The information such as part content, address, time, classifying intelligently integrate similar case and reduce the redundancy that system accepts event.
In the present embodiment, the restricted person of accepting manual read speed is handled in order to solve reported event, event assigns dependence
It is limited by artificial treatment effeciency in the case where magnanimity environment-protection artificial reported event is accepted in the person's of accepting professional ability and is easy to make
It is overstock at event handling.Described " merging data is sent to according to classification and accepts end " specifically includes the following steps:
Merging data is associated with similar history by event keyword and reports event data and preset rules；
Acquisition association is corresponding to accept information, and the information that accepts includes accepting measure, accepting process and cooperation department；
By merging data and accepts information and be sent to and accept end.
By the way that merging data is carried out to report event data and preset rules to be associated with similar history, then basis
The association carries out accepting information accordingly to merging data correspondence, then by merging data and accepts information and is sent to and accept end,
It returns result to the person of accepting and is manually adjusted or be automatically assigned to each department and grid person, can be reported according to history
The information that accepts of data accepted in information and preset rules to reported event, intelligent association accept measure, effectively improve environmental protection
The event of the event person of accepting accepts efficiency.
In another embodiment, a kind of storage medium 210 is stored with computer program in the storage medium 210,
It is characterized in that, the computer program executes following steps when being run by processor:
It extracts history to report the characteristic value of event data and report event data that label is arranged history, according to the spy of extraction
Value indicative and the label of setting are trained to obtain event category model；
When getting new reported event data, event keyword is distributed to new reported event data, and extract new
Reported event data characteristic value；
According to the event keyword of distribution and the characteristic value of extraction, by event category model to new reported event data
Sorted out and forms merging data after being merged；
Merging data is sent to according to classification and accepts end.
By carrying out establishing event category model using history reported event as sample, carry out for logical to environmentalist
It crosses the event that manual type reports to be identified, wherein specifically establishing event category model, specific step is as follows:
The exclusive dictionary of reported event is established according to event keyword；
It reports event data as sample using history, reports the content of text of event data to history using full-text search engine
It carries out automatic word segmentation and matches the corresponding exclusive dictionary of reported event, establish history and report reflecting for event data and event keyword
It penetrates；
The characteristic value for extracting history reported event, reports the event keyword of event data to be converted to characteristic value history
Mathematic vector space with initialization weighted value, is classified automatically using k- k-nearest neighbor, forms event category model.
Wherein, event keyword includes event type, event argument, event object.Characteristic value includes the GPS of reported event
Longitude and latitude, report channel, upper journalist, on call time.
Mapping between event data and event keyword is reported by establishing history, history reported event is configured
Corresponding label such as establishes the exclusive dictionary A of reported event according to event keyword a, then obtains history and reports event data, with
It is sample that history, which reports event data, reports the content of text of event data to the history as sample using full-text search engine
The exclusive dictionary of the corresponding reported event of Auto-matching is carried out, i.e., whether retrieved to the content of text of sample includes to report thing
Keyword corresponding to the exclusive dictionary of part such as retrieves when including keyword a, is then matched in dictionary A, establishes history and report
Mapping between event data and event keyword.
And in order to establish optimal classification model, after described " being classified automatically using k- k-nearest neighbor " further include with
Lower step: the duplicate removal result for reporting event data to classify using history automatically adjusts band initialization weighted value as score basis
It is excellent, disaggregated model is generated based on the weighted value after tuning.By the duplicate removal result that reports event data to classify using history as commenting
Point foundation carries out tuning to band initialization weighted value so that weighted value can achieve it is optimal, and then based on the weighted value after tuning
Optimal disaggregated model can be generated, keep the classification to new reported event data more accurate.
And when environmentalist reports new reported event data, event is allocated to new reported event data automatically
Then keyword extracts the characteristic value etc. in environmentalist's reported event data, then according to event category model automatic clustering
Merging forms merging data, is then sent to and accepts end, the data in environmentally friendly event manually reported by automatic identification, such as thing
The information such as part content, address, time, classifying intelligently integrate similar case and reduce the redundancy that system accepts event.
In the present embodiment, the restricted person of accepting manual read speed is handled in order to solve reported event, event assigns dependence
It is limited by artificial treatment effeciency in the case where magnanimity environment-protection artificial reported event is accepted in the person's of accepting professional ability and is easy to make
It is overstock at event handling.Described " merging data is sent to according to classification and accepts end " specifically includes the following steps:
Merging data is associated with similar history by event keyword and reports event data and preset rules；
Acquisition association is corresponding to accept information, and the information that accepts includes accepting measure, accepting process and cooperation department；
By merging data and accepts information and be sent to and accept end.
By the way that merging data is carried out to report event data and preset rules to be associated with similar history, then basis
The association carries out accepting information accordingly to merging data correspondence, then by merging data and accepts information and is sent to and accept end,
It returns result to the person of accepting and is manually adjusted or be automatically assigned to each department and grid person, can be reported according to history
The information that accepts of data accepted in information and preset rules to reported event, intelligent association accept measure, effectively improve environmental protection
The event of the event person of accepting accepts efficiency.
It should be noted that being not intended to limit although the various embodiments described above have been described herein
Scope of patent protection of the invention.Therefore, it based on innovative idea of the invention, change that embodiment described herein is carried out and is repaired
Change, or using equivalent structure or equivalent flow shift made by description of the invention and accompanying drawing content, it directly or indirectly will be with
Upper technical solution is used in other related technical areas, is included within scope of patent protection of the invention.
Claims (10)
1. a kind of processing method of magnanimity environment-protection artificial reported event data, which comprises the following steps:
It extracts history to report the characteristic value of event data and report event data that label is arranged history, according to the characteristic value of extraction
And the label of setting is trained to obtain event category model；
When getting new reported event data, event keyword is distributed to new reported event data, and extract newly upper
Report the characteristic value of event data；
According to the event keyword of distribution and the characteristic value of extraction, new reported event data are carried out by event category model
Sort out and forms merging data after merging；
Merging data is sent to according to classification and accepts end.
2. the processing method of magnanimity environment-protection artificial reported event data according to claim 1, which is characterized in that described " to mention
It takes history to report the characteristic value of event data and reports event data that label is set history, according to the characteristic value and setting of extraction
Label be trained to obtain event category model " specifically includes the following steps:
The exclusive dictionary of reported event is established according to event keyword；
It reports event data as sample using history, reports the content of text of event data to carry out history using full-text search engine
Automatic word segmentation matches the corresponding exclusive dictionary of reported event, establishes the mapping that history reports event data and event keyword；
History is reported the event keyword of event data and characteristic value to be converted to band just by the characteristic value for extracting history reported event
The mathematic vector space of beginningization weighted value, is classified automatically using k- k-nearest neighbor, forms event category model.
3. the processing method of magnanimity environment-protection artificial reported event data according to claim 2, which is characterized in that described " to make
Classified automatically with k- k-nearest neighbor " further comprising the steps of later:
The duplicate removal result for reporting event data to classify using history carries out tuning to band initialization weighted value automatically as score basis,
Disaggregated model is generated based on the weighted value after tuning.
4. the processing method of magnanimity environment-protection artificial reported event data according to claim 1, which is characterized in that the feature
The GPS longitude and latitude of value including reported event, report channel, upper journalist, on call time；The event keyword includes event class
Type, event argument, event object.
5. the processing method of magnanimity environment-protection artificial reported event data according to claim 1, which is characterized in that described " by
Merging data is sent to according to classification accepts end " specifically includes the following steps:
Merging data is associated with similar history by event keyword and reports event data and preset rules；
Acquisition association is corresponding to accept information, and the information that accepts includes accepting measure, accepting process and cooperation department；
By merging data and accepts information and be sent to and accept end.
6. a kind of storage medium, computer program is stored in the storage medium, which is characterized in that the computer program quilt
Processor executes following steps when running:
It extracts history to report the characteristic value of event data and report event data that label is arranged history, according to the characteristic value of extraction
And the label of setting is trained to obtain event category model；
When getting new reported event data, event keyword is distributed to new reported event data, and extract newly upper
Report the characteristic value of event data；
According to the event keyword of distribution and the characteristic value of extraction, new reported event data are carried out by event category model
Sort out and forms merging data after merging；
Merging data is sent to according to classification and accepts end.
7. storage medium according to claim 6, which is characterized in that the processor executes the step and " extracts in history
Report the characteristic value of event data and report event data that label is set history, according to the characteristic value of extraction and the label of setting into
Row training obtains event category model " when, specifically execute following steps:
The exclusive dictionary of reported event is established according to event keyword；
It reports event data as sample using history, reports the content of text of event data to carry out history using full-text search engine
Automatic word segmentation matches the corresponding exclusive dictionary of reported event, establishes the mapping that history reports event data and event keyword；
History is reported the event keyword of event data and characteristic value to be converted to band just by the characteristic value for extracting history reported event
The mathematic vector space of beginningization weighted value, is classified automatically using k- k-nearest neighbor, forms event category model.
8. storage medium according to claim 8, which is characterized in that it is " most adjacent using k- that the processor executes the step
Nearly algorithm is classified automatically " following steps are also executed later:
The duplicate removal result for reporting event data to classify using history carries out tuning to band initialization weighted value automatically as score basis,
Disaggregated model is generated based on the weighted value after tuning.
9. storage medium according to claim 6, which is characterized in that the characteristic value include reported event GPS longitude and latitude,
Report channel, upper journalist, on call time；The event keyword includes event type, event argument, event object.
10. storage medium according to claim 6, which is characterized in that the processor executes the step " by merging data
It is sent to according to classification and accepts end " when, specifically execute following steps:
Merging data is associated with similar history by event keyword and reports event data and preset rules；
Acquisition association is corresponding to accept information, and the information that accepts includes accepting measure, accepting process and cooperation department；
By merging data and accepts information and be sent to and accept end.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110336706A (en) * | 2019-07-23 | 2019-10-15 | 中国工商银行股份有限公司 | Network message method for transmission processing and device |
| CN110807726A (en) * | 2019-11-12 | 2020-02-18 | 软通动力信息技术有限公司 | Method, device, equipment and storage medium for processing reported event |
| CN111256757A (en) * | 2020-02-25 | 2020-06-09 | 深圳哈维生物医疗科技有限公司 | Medical equipment monitoring system and method based on cloud computing |
| CN111311908A (en) * | 2020-02-18 | 2020-06-19 | 青岛海信网络科技股份有限公司 | Method and device for identifying and processing repeated traffic information |
| CN113537691A (en) * | 2021-05-09 | 2021-10-22 | 武汉兴得科技有限公司 | Big data public health event emergency command method and system |
| CN113535959A (en) * | 2021-07-29 | 2021-10-22 | 长三角信息智能创新研究院 | Automatic event distribution method for primary treatment |
| CN113723053A (en) * | 2020-12-28 | 2021-11-30 | 京东城市(北京)数字科技有限公司 | Event aided decision-making method and device, electronic equipment and storage medium |
| CN113722356A (en) * | 2020-12-28 | 2021-11-30 | 京东城市(北京)数字科技有限公司 | Processing method and device for reporting event, electronic equipment and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170330396A1 (en) * | 2014-08-07 | 2017-11-16 | Compucar Car Computers Ltd. | System and method for providing optimal state indication of a vehicle |
| CN108229910A (en) * | 2017-12-14 | 2018-06-29 | 四川虹慧云商科技有限公司 | A kind of classification processing method of resident's reported event |
| CN108874968A (en) * | 2018-06-07 | 2018-11-23 | 平安科技（深圳）有限公司 | Risk management data processing method, device, computer equipment and storage medium |
-
2018
- 2018-12-24 CN CN201811584065.XA patent/CN109657063A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170330396A1 (en) * | 2014-08-07 | 2017-11-16 | Compucar Car Computers Ltd. | System and method for providing optimal state indication of a vehicle |
| CN108229910A (en) * | 2017-12-14 | 2018-06-29 | 四川虹慧云商科技有限公司 | A kind of classification processing method of resident's reported event |
| CN108874968A (en) * | 2018-06-07 | 2018-11-23 | 平安科技（深圳）有限公司 | Risk management data processing method, device, computer equipment and storage medium |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110336706A (en) * | 2019-07-23 | 2019-10-15 | 中国工商银行股份有限公司 | Network message method for transmission processing and device |
| CN110336706B (en) * | 2019-07-23 | 2022-09-13 | 中国工商银行股份有限公司 | Network message transmission processing method and device |
| CN110807726A (en) * | 2019-11-12 | 2020-02-18 | 软通动力信息技术有限公司 | Method, device, equipment and storage medium for processing reported event |
| CN111311908A (en) * | 2020-02-18 | 2020-06-19 | 青岛海信网络科技股份有限公司 | Method and device for identifying and processing repeated traffic information |
| CN111256757A (en) * | 2020-02-25 | 2020-06-09 | 深圳哈维生物医疗科技有限公司 | Medical equipment monitoring system and method based on cloud computing |
| CN113723053A (en) * | 2020-12-28 | 2021-11-30 | 京东城市(北京)数字科技有限公司 | Event aided decision-making method and device, electronic equipment and storage medium |
| CN113722356A (en) * | 2020-12-28 | 2021-11-30 | 京东城市(北京)数字科技有限公司 | Processing method and device for reporting event, electronic equipment and storage medium |
| CN113537691A (en) * | 2021-05-09 | 2021-10-22 | 武汉兴得科技有限公司 | Big data public health event emergency command method and system |
| CN113535959A (en) * | 2021-07-29 | 2021-10-22 | 长三角信息智能创新研究院 | Automatic event distribution method for primary treatment |
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Application publication date: 20190419 |