CN115809256B

CN115809256B - Public security management integrated information system and visual display method

Info

Publication number: CN115809256B
Application number: CN202310148482.4A
Authority: CN
Inventors: 常海峰; 陈海峰; 王星; 刘洋; 陈成领
Original assignee: Zhongguancun Smart City Co Ltd
Current assignee: Zhongguancun Smart City Co Ltd
Priority date: 2023-02-22
Filing date: 2023-02-22
Publication date: 2023-06-06
Anticipated expiration: 2043-02-22
Also published as: CN115809256A

Abstract

The embodiment of the disclosure discloses a public security management integrated information system and a visual display method. One embodiment of the system comprises: the service development server cluster is configured to: performing research analysis on public security management data; the business-associated retrieval model building server cluster is configured to: constructing an associated retrieval model for the public security management data; the target object relationship model building server cluster is configured to: constructing a relational network model for the public security management data; the data visualization query server cluster is configured to: visual query result display is carried out on the associated retrieval data and the relationship data; the visual presentation server cluster is configured to: and visually displaying the associated retrieval data and the relationship data. According to the embodiment, centralized management of public security management data and display of information analysis results can be achieved, and basic functions are highly shared, so that public security management, research and judgment treatment efficiency and convenience for people service accuracy are improved.

Description

Public security management integrated information system and visual display method

Technical Field

The embodiment of the disclosure relates to the technical field of computers, in particular to a public security management integrated information system and a visual display method.

Background

The public security management integrated information system is an important system for the information management and work development of institutions, and plays a very important role in ensuring social security. For data processing of public security management information, the following methods are generally adopted: the main data processing mode of public security management information is realized by manual auditing and independent analysis of multiple departments, and in addition, simple basic level business data is called to carry out data analysis.

However, the inventors have found that when the above-described manner is adopted, there are often the following technical problems:

firstly, the data processing period is longer, the data association sharing is weaker, the using convenience of target personnel is poor, and the visualization capability is insufficient.

Secondly, the accuracy of the track accompanying analysis of the target personnel is low, and only the spatial information of the track information is considered.

Thirdly, the correlation analysis of the colony event has low accuracy, and the aggregation point cannot be accurately predicted.

The above information disclosed in this background section is only for enhancement of understanding of the background of the inventive concept and, therefore, may contain information that does not form the prior art that is already known to those of ordinary skill in the art in this country.

Disclosure of Invention

The disclosure is in part intended to introduce concepts in a simplified form that are further described below in the detailed description. The disclosure is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

Some embodiments of the present disclosure propose a peace management integrated information system to address one or more of the technical problems mentioned in the background section above.

In a first aspect, some embodiments of the present disclosure provide a public security management integrated information system comprising: the system comprises a service research judging server cluster, a service association retrieval model constructing server cluster, a target object relation model constructing server cluster, a data visual query server cluster and a visual display server cluster, wherein: the service research and judgment server cluster is respectively in communication connection with the service association search model construction server cluster and the target object relation model construction server cluster, wherein the service research and judgment server cluster is configured to: performing research analysis on public security management data; the service association search model building server cluster is respectively in communication connection with the data visualization query server cluster and the visualization display server cluster, wherein the service association search model building server cluster is configured to: constructing an associated retrieval model for public security management data, and providing associated retrieval data for the data visual query server cluster and the visual display server cluster; the target object relation model building server cluster is respectively in communication connection with the data visual query server cluster and the visual display server cluster, wherein the target object relation model building server cluster is configured to: constructing a relational network model for the public security management data, and providing relational data for the data visual query server cluster and the visual display server cluster; the data visualization query server cluster is configured to: building a server cluster according to the service association retrieval model, building association retrieval data and relationship data sent by the server cluster according to the target object relationship model, and displaying visual comprehensive query results of the association retrieval data and the relationship data; the visual presentation server cluster is configured to: and constructing a server cluster according to the service association retrieval model, constructing association retrieval data and relationship data sent by the server cluster according to the target object relationship model, and visually displaying the association retrieval data and the relationship data.

In a second aspect, some embodiments of the present disclosure provide a visual display method of a public security management integrated information system, applied to the public security management integrated information system described in the first aspect, including: obtaining public security management data for a plurality of data sources; extracting elements from the public security management data through the data source management server to obtain a special service database; performing research analysis on the special service database through the service research server cluster to obtain a research result; constructing a server cluster through the service association retrieval model and constructing the server cluster through the target object relation model, and carrying out statistical analysis on the research and judgment result to obtain a statistical analysis result; and carrying out visual query and statistical display on the statistical analysis result through the data visual query server cluster and the visual display server cluster.

In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors, cause the one or more processors to implement the method as described in any of the implementations of the first aspect.

In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium having a computer program stored thereon, wherein the program when executed by a processor implements a method as described in any of the implementations of the first aspect.

The above embodiments of the present disclosure have the following advantages: the public security management comprehensive information system of some embodiments of the present disclosure can realize centralized management of information resources, achieve high integration of information analysis display capability, realize high sharing of basic services, and promote public security management, study and judgment treatment efficiency. Specifically, the reason for the low disposal efficiency of the related public security study is that: the processing period of the public security management data is longer, the association sharing among the public security management data is weaker, the convenience of people in use is poor, and the visual display of the public security management data is insufficient. Based on this, the public security management integrated information system of some embodiments of the present disclosure includes: the system comprises a service research judging server cluster, a service association retrieval model constructing server cluster, a target object relation model constructing server cluster, a data visual query server cluster and a visual display server cluster, wherein: the service research and judgment server cluster is respectively in communication connection with the service association search model construction server cluster and the target object relation model construction server cluster, wherein the service research and judgment server cluster is configured to: and performing research analysis on the public security management data. The business research judgment server cluster is used for carrying out basic data processing on the public security management data and associated retrieval among the public security management data, so that the subsequent model building analysis on the processed data is facilitated, and deeper associated relations are mined. The service association search model building server cluster is respectively in communication connection with the data visualization query server cluster and the visualization display server cluster, wherein the service association search model building server cluster is configured to: and constructing an associated retrieval model for the public security management data, and providing associated retrieval data for the data visual query server cluster and the visual display server cluster. The target object relation model building server cluster is respectively in communication connection with the data visual query server cluster and the visual display server cluster, wherein the target object relation model building server cluster is configured to: and constructing a relational network model for the public security management data, and providing relational data for the data visual query server cluster and the visual display server cluster. The model construction and training are carried out on the processed public security management data through specific business conditions, deeper association relations among the public security management data are mined, and the public security management research and judgment processing efficiency and the convenience service accuracy are improved. The data visualization query server cluster is configured to: and constructing a server cluster according to the service association retrieval model, constructing association retrieval data and relationship data sent by the server cluster according to the target object relationship model, and displaying visual comprehensive query results of the association retrieval data and the relationship data. The visual presentation server cluster is configured to: and constructing a server cluster according to the service association retrieval model, constructing association retrieval data and relationship data sent by the server cluster according to the target object relationship model, and visually displaying the association retrieval data and the relationship data. The analysis results obtained by the service research and judgment server cluster, the service association retrieval model construction server cluster and the target object relation model construction server cluster are visually displayed, so that the requirements of target personnel on security information interaction are met conveniently. Therefore, the public security management comprehensive information system can realize centralized management of information resources, achieve high fusion of information analysis display capability, realize high sharing of basic services and improve public security management, study and judgment treatment efficiency.

Drawings

The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. The same or similar reference numbers will be used throughout the drawings to refer to the same or like elements. It should be understood that the figures are schematic and that elements and components are not necessarily drawn to scale.

FIG. 1 is a schematic structural diagram of some embodiments of a peace management integrated information system according to the present disclosure;

FIG. 2 is a flow chart of some embodiments of a visual presentation method of a peace management integrated information system according to the present disclosure;

fig. 3 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.

It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.

It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, servers, or units and are not intended to limit the order or interdependence of functions performed by the devices, servers, or units.

It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.

The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

Referring to fig. 1, a structural schematic diagram of some embodiments of a peace management integrated information system according to the present disclosure is shown. As shown in fig. 1, the public security management integrated information system provided by the present disclosure may include: the system comprises a service research judging server cluster 1, a service association retrieval model constructing server cluster 2, a target object relation model constructing server cluster 3, a data visual query server cluster 4 and a visual display server cluster 5.

In some embodiments, the service research server cluster 1 is in communication connection with the service association search model building server cluster 2 and the target object relationship model building server cluster 3, respectively. Here, the manner in which the service research and judgment server cluster 1 is communicatively connected to the service association search model building server cluster 2 and the target object relationship model building server cluster 3, respectively, is not limited. For example, the service research and determination server cluster 1 may be communicatively connected to the service association search model building server cluster 2 and the target object relationship model building server cluster 3 via a specific API (Application Programming Interface ) interface. The service research and judgment server cluster 1 may be configured to perform research and judgment analysis on the Zhi' an management data by adopting an analysis algorithm. The public security management data may be data from a plurality of data sources related to social security control data. For example, the public security management data may include: demographic information data, various police jurisdiction location information data, city planning information data, vehicle information data, financial data, video surveillance data, telecom operation data, real estate data, online shopping information data, web browsing data, and the like. The analysis algorithm may be an association rule algorithm. In practice, the service association search model building server cluster may be a server cluster that performs association analysis on the public security management data by using association rules in association with service scenarios. The service association search model may be a machine learning model. The machine learning model may include, but is not limited to: rule-based association analysis model, big data-based association analysis model. For example, the service association search model building server cluster may include: the system comprises a data source management server, a data analysis management server, an index calculation model construction server, a topic analysis model construction server and a topic analysis model construction server. For example, in the business scenario of the target scenic spot public security special project, the business association retrieval model can be used for counting the number of times of the target personnel, the target articles and the alarms, and is the same as the previous period. The number of alarms can be the sum of the number of alarms of related personnel to a specific alarm point, the number of alarms of the control vehicle and the number of alarms of police officers. The relevant person may be a target attraction player, a target attraction worker, or the like.

In some embodiments, the service association search model building server cluster is respectively in communication connection with the data visualization query server cluster and the visualization presentation server cluster. Here, the manner in which the service-related search model building server cluster is communicatively connected to the data visual query server cluster and the visual presentation server cluster, respectively, is not limited. For example, the service association search model building server cluster may be communicatively connected to the data visualization query server cluster and the visualization presentation server cluster through specific API interfaces, respectively. The service association search model building server cluster is configured to: and constructing a relevant retrieval model for the public security management data, and providing analysis results for the data visual query server cluster and the visual display server cluster. For example, the service association search model building server cluster may be a server cluster for building an association relationship by an association relationship between peace management data. In practice, the executing body may first construct a case knowledge graph according to text information. And secondly, carrying out random walk sampling on the node set data constructed by the case knowledge graph to acquire a plurality of sequence data. And thirdly, performing model training on the plurality of sequence data by using a word conversion vector algorithm to obtain an updated target model. The target model may be a model obtained by converting words in a plurality of sequence data into a representation form of vectors through an input layer to obtain word vectors, calculating an accumulated sum of the word vectors output by the input layer by a hidden layer to obtain a total vector, connecting the total vector with each non-leaf node of a Huffman tree of the output layer, constructing the Huffman tree on the total vector according to a semantic relation and a context relation, and performing probability calculation on the Huffman tree through an energy function. And then, acquiring target text information, and analyzing the target text information through the target model to construct a knowledge graph to be searched. The target text information may be text information corresponding to case information obtained from the public security management data. And searching in the case knowledge graph according to the knowledge graph to be searched to acquire case information related to the knowledge graph to be searched. And finally, acquiring a model of the output case information according to the first similarity and the second similarity of the case information.

In some embodiments, the target object relationship model building server cluster is respectively in communication connection with the data visualization query server cluster and the visualization presentation server cluster. Here, the manner in which the target object relationship model building server cluster is communicatively connected to the data visualization query server cluster and the visualization presentation server cluster, respectively, is not limited. For example, the target object relationship model building server cluster may be communicatively connected to the data visualization query server cluster and the visualization presentation server cluster through specific API interfaces, respectively. The target object relationship model building server cluster is configured to: and constructing a relational network model for the public security management data, and providing analysis results for the visual display server cluster and the data visual query server cluster. In practice, the target object relationship model building server cluster may be a building server cluster of a target object relationship network generated by performing association search on data of different aspects of the target object. Wherein the data of the different aspects may include at least one of: cases, people, places, group events associated with the target object. For example, the target object relationship model building server cluster may be a server cluster that performs association search on cases, persons, places, group events, space-time relationships, and behavior tracks associated with the target object, and generates topological relationships between cases, persons, places, group events, space-time relationships, and behavior tracks associated with the target object. The target object relationship model building server cluster may include: the system comprises a target personnel relationship network model building server, a case information relationship network model building server, a target place relationship network model building server, a group event relationship network model building server, a space-time analysis relationship network model building server and a track analysis network model building server.

In some embodiments, the data visualization query server cluster described above is configured to: and constructing a server cluster according to the service association retrieval model, constructing a statistical analysis result sent by the server cluster according to the target object relation model, and displaying a visual comprehensive query result of the statistical analysis result. The statistical analysis result may be an associated search result of each case, person and police condition. The statistical analysis result may be an analysis result of a relational network of each target person, target location, case information, and the like. The police situation can be the phenomenon that police dispatch posts correspondingly dispatch police to conduct social security maintenance after crime events occur or alarm information is received. In practice. The execution body can display the query result in a graphical visualization mode through the received query request of the query personnel. The query request may be a query request for a specific location name. The query result may be a topological relation network including the place name as a center and other case information, place information and personnel information related to the place name.

In some embodiments, the visual presentation server cluster is configured to: and constructing a server cluster according to the service association retrieval model, constructing a statistical analysis result sent by the server cluster according to the target object relation model, and visually displaying the statistical analysis result. The analysis result may be a search result related to each case, person, police situation, etc., or may be an analysis result of a relational network of each target person, target location, case information, etc. In practice, the analysis results are visually displayed by using a visualization tool or a visualization method. Wherein the visualization tool may be a Tableau. The visualization method may be an E-charts chart.

Optionally, the service research and judgment server cluster includes: the system comprises a data source management server, a data analysis management server, an index calculation model construction server, a topic analysis model construction server and a topic analysis model construction server.

In some embodiments, the data source management server is configured to: and processing public security management data of different data sources and extracting keyword data to obtain a special service database. The public security management data of the different data sources can be stored public security management data from different areas and different departments. The specialized business database may be a specialized business database created for different people. For example, the proprietary business database may be a business database of associated public security database tables and judicial data tables created for community rectification personnel. The community correction personnel can be criminals with lighter crimes, less subjective maliciousness and less social hazard or personnel with repentance performance and no harm to the society after supervision and transformation. The keyword data may include at least one of: anti-terrorism, robbery and burglary. The processing of the public security management data can be denoising, cleaning and unifying data formats of the public security management data.

In some embodiments, the data analysis management server is communicatively coupled to the data source management server. Here, the manner in which the data analysis management server is communicatively connected to the data source management server is not limited. For example, the data analysis management server may be communicatively connected to the data source management server via a specific API interface. The data analysis management server is configured to: and carrying out statistical analysis on a plurality of data tables in a public security management service scene database in the special service database sent by the data source management server. The public security management service scene database may be a database for storing public security management data according to service scenes. In practice, the data analysis management server may determine, through the association information, an average value and an accumulated total of a plurality of tables corresponding to the association information. Wherein, the association relationship can be the identity card number of the personnel.

In some embodiments, the topic analysis model building server is in communication with the data source management server. Here, the manner in which the topic analysis model building server is communicatively connected to the data source management server is not limited. For example, the topic analysis model building server may be communicatively connected to the data source management server via a specific API interface. The topic analysis model building server is configured to: and carrying out statistical analysis on a plurality of data tables in the special public security service data in the special service database sent by the data source management server. In practice, the thematic analysis model construction server can be a server for analyzing the total alarm amount and the homonymous analysis, the total alarm amount and the homonymous analysis of the control vehicles, the control person alarm amount and the homonymous analysis, the distribution control vehicles and the control person analysis around the target area, and the distribution alarm period analysis around the target area. Wherein, the special public security service data in the special service database can comprise at least one of the following: police officer information, police officer number and patrol time period for patrol dispatch of the target area by police officers.

In some embodiments, the topic analysis model building server is in communication with the data source management server. Here, the manner in which the topic analysis model building server is communicatively connected to the data source management server is not limited. For example, the topic analysis model building server may be communicatively coupled to the data source management server via a specific API interface. The topic analysis model building server described above is configured to: and carrying out statistical analysis on the alarm condition data in the special service database sent by the data source management server. In practice, the topic analysis model construction server sends out servers for forward ranking or reverse ranking of the first 5 week and week trend analysis of the police information data through analysis of total quantity and homonymy of the police information data, duty ratio of the target police information data, total quantity and homonymy of the police information data in the public security management data. The topic analysis model construction server can better support daily public security management data requirements. The target alert data may be a daily alert event. Daily alerts may include at least one of: fighting, reporting and crowd events.

In some embodiments, the index calculation model building server is communicatively coupled to the data source management server. Here, the manner in which the index calculation model building server is communicatively connected to the data source management server is not limited. For example, the topic analysis model building server may be communicatively connected to the data source management server via a specific API interface. The index calculation model construction server is configured to: and carrying out statistical analysis on the target person, the target place and the target object in the special service sent by the data source management server. In practice, the index calculation model construction server provides total and homonymous analysis, target person duty ratio, total and homonymous analysis, total and distribution analysis of target places through data information in public security management, and establishes a server for ranking positive or reverse orders of important articles of each dispatched safety inspection. The target personnel can be personnel which are seriously managed by public security authorities and have the harm to national security or public security suspicion. For example, the target person may be a person engaged in spying. The target site may be a relatively personnel intensive site. For example, the target sites may be entertainment sites and service sites. The target item may be an item having certain dangerous properties. For example, the target item may be a control knife.

Optionally, the service association search model builds a server cluster, including: case information associated search model construction server, personnel information associated search model construction server and warning information associated search model construction server.

In some embodiments, the case information association retrieval model construction server is configured to: and extracting keywords of law enforcement and case handling types and properties in the special business database, and performing model training on the keywords to obtain analysis results. The law enforcement type may be a public security event law enforcement type or a group access law enforcement type. The property key may include at least one of: criminals, civil and administrative. For example, the case information related search model building server may train the keywords of the case information by using a keyword extraction model to obtain a keyword set of the same kind of case information. And then, carrying out visual display on the obtained keyword set. And finally, determining the case information corresponding to the keywords with the similarity of more than or equal to 0.85 in the keyword set of the same type of cases as the case information of the same type, and constructing a server according to a model for processing the case information with the similarity of more than or equal to 0.85 according to the processing process of the case information. The keyword extraction model may be a mask-based unsupervised keyword extraction (MDERank) model, among others. The visual presentation of the keyword sets may be presented in the form of a dictionary.

In some embodiments, the above-described person information association retrieval model construction server is configured to: and extracting case keywords related to security management types from the special service database, and performing model training on the keywords to obtain analysis results. The personnel information association search construction server may be a model construction server for training a keyword set of a public security management event associated with a target person by using a keyword extraction model to obtain the keyword set of the public security management event corresponding to the target person, and visually displaying the keyword set. The keyword extraction model may be a mask-based unsupervised keyword extraction (MDERank) model, among others. The visual presentation of the keyword sets may be presented in the form of a dictionary. The case related to the peace management type may be a case constituted by violating peace management actions. For example, a peace management type case may be a case that disturbs the behavior of public order.

In some embodiments, the alert information association search model building server is configured to: and extracting the related alert description keywords in the special service database, and performing model training according to the alert description keywords to obtain a keyword set related to alert information. The warning information associated search model construction server obtains warning keyword sets corresponding to different warning information by extracting warning description keywords related to the warning information in the special service database, and the model construction server performs visual display on the keyword sets. The alert information association search model may be a mask-based unsupervised keyword extraction (MDERank) model. The alert description keywords may be keywords obtained by extracting keywords from alert cases. For example, the alert description keywords may include at least one of: alarming, seeking help and complaining.

Optionally, the target object relation model building server cluster includes: the system comprises a target personnel relationship network model building server, a case information relationship network model building server, a target place relationship network model building server, a group event relationship network model building server, a space-time analysis relationship network model building server and a track analysis network model building server.

In some embodiments, the above-described target person relationship network model building server is configured to: generating a target personnel relationship analysis result through personal information inquiry, and checking information of the associated case and the associated place according to the target personnel relationship analysis result. The target person relationship network model building server may be a relationship extraction model building server which uses a target person as a main node and builds relationship extraction models by using person information, case information and place information related to the target person as other nodes through association query. The target person relationship network model may be a machine learning model. The machine learning model may be a relationship extraction model.

In some embodiments, the case information relationship network model building server is configured to: generating a case information relation analysis result through case information inquiry, and checking data information of target personnel and target places related to the case information according to the case information relation analysis result. The case information relationship network model building server may be a relationship extraction building server which uses target case information as a main node, and builds relationship by searching for a target person and a target place related to the target case information as other nodes through association. The target case information may be robbery case information. The case information relationship network model may be a machine learning model. The machine learning model may be a relationship extraction model.

In some embodiments, the target site relationship network model building server is configured to: generating a target place relation analysis result through target place information inquiry, and checking information of target personnel associated with the target place according to the target place relation analysis result. And the data source table query item is supported to generate a target place analysis result. The target location relationship network model construction server may be a relationship extraction construction server which uses a target location as a central node, and searches for location information associated with the target location and target personnel information as knowledge maps constructed by other nodes. The target site relationship network model may be a machine learning model. The machine learning model may be a relationship extraction model.

In some embodiments, the above-described social event relationship network model building server is configured to: generating a group event relation analysis result through personal information inquiry, and checking information of target personnel and associated group organization associated with the target group event according to the group event relation analysis result. The analysis result of the group event relation supports the query term of the data source table to generate the analysis result of the group event. The above-mentioned group event relation network model construction server may be a relation network model server which uses the group event as a central node and inquires the knowledge graph constructed for other nodes by the target personnel related to the group event and the group organization. The social event relationship network model may be a machine learning model. The machine learning model may be a relationship extraction model. The analysis result of the relationship between the crowd events can be the crowd events participated by the personnel corresponding to the inquiry personal information through the identification card number in the personal information. A social event may be a variety of events that are engaged by multiple people that have a significant negative impact on social order and social stability. For example, the crowd event may be a parade showing event.

In some embodiments, the spatiotemporal analysis relational network model building server described above is configured to: generating a space-time analysis relation result by inquiring the place and the case information controlled by the public security, and checking the related case information and the information of the target personnel according to the space-time analysis relation result. The space-time analysis relation result supports the data source table query term to generate a space-time analysis relation analysis result. In practice, the space-time analysis relation network model building server can be a building server for obtaining the relevant cases and related personnel associated with the places and case information controlled by public security through data collision and relevant retrieval processing of the places, the time information and the space information of the case information controlled by public security and displaying analysis results in a visual topological graph.

In some embodiments, the trajectory analysis network model building server is configured to: track analysis results are generated by constructing personal information queries. The track analysis result supports the data source table query item to generate the track analysis result. In practice, the track analysis network model building server can obtain the action track of the target person in a certain time by associating a plurality of public security management data tables with personal information, and the model building server can display the action track on a map. Wherein the certain time may be 5 days. The plurality of public security management data tables may include at least one of: consumption information of target personnel, vehicle information, communication information and case information. The track analysis network model construction server can also construct a multi-person track, wherein the multi-person track can be presented in a mode of a knowledge graph vector diagram.

Optionally, the data visualization query server cluster includes: the system comprises a unified report management server, a comprehensive query management server, a statistical analysis management server and a statistical result display server.

In some embodiments, the unified report management server is configured to: and the created fixed report or the flexible report is sent to each level of organization departments to be filled by the organization departments. Wherein, the fixed report forms are report forms which can be created according to report form formats required by the security department. A flexible report is a report that can be automatically created by dynamic requirements. After the flexible report is automatically created, the execution main body can send the flexible report to each department at regular time according to the requirement and collect the content of the flexible report which is filled and reported by each department. The execution body can also appoint to send a plurality of different departments and collect the contents of the flexible report reported by the departments.

In some embodiments, the integrated query management server is configured to: and providing query result display for public security management data of different data sources, the research analysis results sent by the service research server cluster, the analysis results sent by the service association search model building server cluster and the analysis results sent by the target object relation model building server cluster through a unified interface. The query result presentation may be statistical data such as loop ratio, constant ratio, threshold, color threshold, multi-dimensional setting, etc. of the analysis result. In practice, the comprehensive query management server can acquire public security management data through an internal data bus, associate a plurality of data tables, and perform association query on intersections, union and complement of the plurality of data tables. The integrated query management server described above may create a query template. The query template may be a template that generates a query template by selecting a field to be queried and a field to be displayed. The execution body may also perform classification management on the template.

In some embodiments, the statistical analysis management server is configured to: and carrying out multidimensional statistical analysis on the public security management data of the different data sources, the research analysis results sent by the business research server cluster, the analysis results sent by the business association search model building server cluster and the analysis results sent by the target object relation model building server cluster through a unified interface. In practice, the statistical analysis management server can realize multidimensional association of query information through inquiring single-table and multi-table association query, and provide multi-data source support of a query target. Meanwhile, the statistical analysis management server can sum and average the public security management data and the data included in the data table, so that the data processing efficiency is improved. The statistical analysis management server can also carry out corresponding custom calculation solution on the public security management data and the data included in the data table according to specific conditions.

In some embodiments, the statistics presentation server is configured to: and displaying the public security management data of the different data sources, the research analysis results sent by the business research server cluster, the analysis results sent by the business association search model building server cluster and the analysis results sent by the target object relation model building server cluster by a unified interface. The visualized statistical result can be displayed in various chart forms such as a pie chart, a bar chart and the like.

Optionally, the visual display server cluster includes: a data content management server and a visual content server.

In some embodiments, the data content management server is configured to: and supporting to call the data table to the data center and displaying the visual contents of the called data table.

In some embodiments, the visual content server is configured to: the visualization template is managed. Wherein, managing the visual template comprises: the visual templates are added, deleted, queried and modified. The visual content server can also detect the video accessed through the API interface and perform double visualization on the data and the video of the abnormal event so as to remind relevant police officers of performing corresponding countermeasure.

With continued reference to fig. 2, a flow 200 of some embodiments of a visual presentation method of a public security management integrated information system according to the present disclosure is shown. The visual display method comprises the following steps:

step 201, obtaining peace management data for a plurality of data sources.

In some embodiments, the execution subject of the visual presentation method (e.g., the public security management integrated information system shown in fig. 1) may acquire public security management data for a plurality of data sources through a wired connection manner or a wireless connection manner. The public security management data of the plurality of data sources can be public security management data of a plurality of departments located in different areas. Different departments may include: criminal police departments, traffic police departments, poison banking departments, and the like.

By way of example, the execution subject can implement flexible deployment of the collection function by adopting the synchronous capability of the adapter between the collection source points and unified automatic allocation and scheduling, and complete the acquisition of the public security management data of a plurality of data sources.

Step 202, element extraction is carried out on public security management data through a data source management server, and a special business database is obtained.

In some embodiments, the execution entity may extract elements of the public security management data through the data source management server to obtain a private service database. The special service database can be a special service database obtained for different people.

As an example, the execution subject may extract key word elements for the service database of the associated public security database table and the judicial database table created by the community corrector, to obtain a specialized service database.

And 203, performing research analysis on the special service database through the service research server cluster to obtain a research result.

In some embodiments, the executing entity may perform a research analysis on the specific service database through the service research server cluster to obtain a research result. The service research and judgment server cluster comprises: the system comprises a data source management server, a data analysis management server, an index calculation model construction server, a topic analysis model construction server and a topic analysis model construction server.

As an example, the executing body may perform statistical analysis on the target person, the target place and the target object by using a statistical analysis algorithm, so as to obtain a statistical analysis result. And a prediction model is adopted to predict the dynamic management and control of the group event, the situation and the risk hidden danger, so that a prediction result is obtained, the group event and the risk hidden danger possibly occurring can be comprehensively grasped, and corresponding measures are timely taken. The predictive model may be a XGBoost (eXtreme Gradient Boosting) model, among others.

And 204, constructing a server cluster through a business association retrieval model and a target object relation model, and carrying out statistical analysis on the research and judgment result to obtain a statistical analysis result.

In some embodiments, the executing body may build a server cluster through a service association search model and a target object relationship model, and perform statistical analysis on the research result to obtain a statistical analysis result. The service association search model builds a server cluster, and the method comprises the following steps: case information associated search model construction server, personnel information associated search model construction server and warning information associated search model construction server. The target object relation model building server cluster comprises: the system comprises a target personnel relationship network model building server, a case information relationship network model building server, a target place relationship network model building server, a group event relationship network model building server, a space-time analysis relationship network model building server and a track analysis network model building server.

As an example, the executing body can perform association search on the case information in the public security management data through an association search algorithm to obtain personnel information and police information associated with the case information, and construct an association knowledge graph so that police personnel can more comprehensively understand the case information. The executing body may first perform keyword extraction on the target alert information data by using a keyword extraction model to obtain a target keyword set corresponding to the target alert information. And secondly, determining case classification information and alarm processing flow of the target alarm information through similarity between each target keyword in the target calculation keyword set and the keyword set of the historical alarm information. The keyword extraction model may be a mask-based unsupervised keyword extraction (MDERank) model, among others.

In some optional implementations of some embodiments, the constructing a server cluster by the service association search model and the constructing a server cluster by the target object relation model, performing modeling analysis on the analysis result to obtain a modeling analysis result may include:

the first step, obtaining first track information of the target person in a preset time interval. Wherein the first track information includes a plurality of first track points, and the first track points include: a first time point and position information of the target person at the first time point. The predetermined time interval may be ten minutes, fifteen minutes, or any other suitable time interval.

As an example, the execution subject may extract the location information of the target person and the time information corresponding to the location information by associating the related data information of the target person to obtain the track information of the target person. The related data information may be consumption information of the target person, bill information, bank card information, etc.

And a second step of acquiring second track information of a plurality of personnel to be detected in the time interval. The second track information includes a plurality of second track points, and the second track points include: a second time point and position information of the target person at the second time point. The predetermined time interval may be ten minutes, fifteen minutes, or any other suitable time interval. The plurality of people to be detected can be people which are multiple occurrences of the target person in a plurality of occasions.

And thirdly, determining a time distance matrix corresponding to the target person and the plurality of persons to be detected according to a plurality of first time points corresponding to the first track information and a plurality of second time points corresponding to the second track information. Wherein the time distance matrix may include a plurality of time distances between the first track information and the second track information. The temporal distance may be a time difference between the first point in time and the second point in time.

As an example, for each first track point in the first track information, a time distance between a first time point in the first track point and a plurality of second time points corresponding to the second track information is calculated, and a plurality of time distances corresponding to the first track points are obtained. A time distance matrix is constructed from the plurality of time distances. For example, if the first track information has m first time points and the second track information has n second time points, the size of the time distance matrix is m rows and n columns. Wherein the element of the ith row and jth column may be a temporal distance between the ith first time point and the jth second time point.

And a fourth step of determining a spatial distance matrix corresponding to the target person and the plurality of persons to be detected according to a plurality of first time points corresponding to the first track information and a plurality of position information corresponding to the second track information. The spatial distance matrix may include a plurality of spatial distances between the first track information and the second track information. The spatial distance may be a distance difference between the position information in the first track point and a plurality of position information corresponding to the second track information.

As an example, for each first track point in the first track information, a spatial distance between a plurality of second position information corresponding to the second track information and a first position information in the first track point is calculated, and a plurality of spatial distances corresponding to the first track points are obtained. A spatial distance matrix is constructed from the plurality of spatial distances. For example, if the first track information has m pieces of first position information and the second track information has n pieces of second position information, the size of the spatial distance matrix is m rows and n columns. Wherein the element of the ith row and the jth column may be a spatial distance before the ith first position information and the jth second position information.

And fifthly, determining a time track matrix by giving the first weight to the time distance matrix and giving the second weight to the space distance matrix. Wherein the sum of the first weight and the second weight is 1. The first weight and the second weight are not specifically required here, and can be determined according to the actual application scenario. For example, the first weight corresponding to the time distance matrix may be set to 0 without requiring the consistency in time. Accordingly, the second weight corresponding to the spatial distance matrix is set to 1.

As an example, the execution body may first perform normalization processing on the temporal distance matrix and the spatial distance matrix to obtain a normalized temporal distance matrix and a normalized spatial distance matrix. And then, carrying out weighted combination on the time distance matrix and the space distance matrix after the normalization processing to obtain a time track matrix.

And a sixth step of determining the similarity between the first track information and the second track information according to the time track matrix. The similarity may be a distance measure of time and space between the first track information and the second track information.

As an example, the above-described execution body may first determine, for a target line in the time trajectory matrix, a first target value of the target line. The first target value may be the smallest number in the target row. Then, a target line in which the first target value is located in the time track matrix is determined, and a second target value in a line having a line number greater than the target line number is determined in a next line number of the target line in the time track matrix. Wherein the second target value may be the smallest number of the numbers in the row whose row number is larger than the target row number. The execution body may be a target column in the time track matrix.

And seventhly, comparing the similarity with a preset accompanying similarity to obtain a comparison result. Wherein, the preset concomitance similarity may be 0.85.

And eighth, determining the person to be detected as an accompanying person in response to determining that the similarity is greater than or equal to a preset accompanying similarity as the comparison result.

And ninth, sending the data information of the accompanying personnel to a client side so as to enable police staff to monitor the accompanying personnel.

The technical scheme and the related content are taken as an invention point of the embodiment of the disclosure, and the second technical problem mentioned in the background art is solved, wherein the accuracy of track accompanying analysis of target personnel is low, and only the space information of track information is considered. ". Factors that lead to lower accuracy of the trajectory-accompanying analysis of the target person tend to be as follows: the concomitant analysis of the trajectory information of the target person only takes into account spatial factors. If the above factors are solved, the accuracy of track accompanying analysis of the target personnel can be improved. In order to achieve the effect, the service association search model is used for constructing a server cluster and the target object relation model is used for constructing the server cluster, modeling analysis is carried out on the analysis result, the modeling analysis result is obtained, and the processing steps are executed: acquiring first track information of the target person within a preset time interval, wherein the first track information comprises a plurality of first track points, and the first track points comprise: a first time point and position information of the target person at the first time point; acquiring second track information of a plurality of people to be detected in the time interval, wherein the second track information comprises a plurality of second track points, and the second track points comprise: a second time point and position information of the target person at the second time point; determining a time distance matrix corresponding to the target person and the plurality of persons to be detected according to a plurality of first time points corresponding to the first track information and a plurality of second time points corresponding to the second track information; determining a space distance matrix corresponding to the target person and the plurality of persons to be detected according to a plurality of first time points corresponding to the first track information and a plurality of position information corresponding to the second track information; determining a time track matrix by giving the first weight to the time distance matrix and giving the second weight to the space distance matrix; determining the similarity between the first track information and the second track information according to the time track matrix; comparing the similarity with a preset accompanying similarity to obtain a comparison result; in response to determining that the comparison result is that the similarity is greater than or equal to a preset accompanying similarity, determining the person to be detected as an accompanying person; and sending the data information of the accompanying personnel to a client so as to enable police staff to monitor the accompanying personnel. Therefore, the similarity of the track information is measured from two aspects of time and space by constructing the time distance matrix and the space distance matrix of the two pieces of track information, so that accompanying personnel can be more accurately determined, the problem of low accuracy of track accompanying analysis of target personnel is effectively solved, the calculation method is simple, and the waste of calculation resources is avoided.

Optionally, the constructing a server cluster by the service association search model and the target object relation model to construct a server cluster, and performing modeling analysis on the analysis result to obtain a modeling analysis result may include:

step one, acquiring the data information of a target personnel database in the special service database. Wherein, the data information may include, but is not limited to, at least one of: name, identification card number, face data image, location, household location, and type of target person.

Step two, obtaining track information of the target personnel according to the data information of the target personnel, wherein the track information comprises the following steps: case information related to the target person, consumption behavior of the target person, and place information to which the target person has gone.

As an example, the executing entity may first associate a plurality of database tables through the identification card number of the target person, to obtain a new database table using the identification card number of the target person as the primary key. The new data table includes the following fields: identification card number, time information, location information, consumption information, related personnel information and related case information. Then, the track information of the target person is drawn through the field information in the new data table.

Thirdly, inquiring a plurality of cases and a plurality of associated persons which are associated with the target person or related to the target person from the special business database according to the data information of the target person.

Fourth, in response to determining that the plurality of associated persons are associated with other target persons, the target recursively queries other plurality of associated persons having case associations and venue associations with the other target persons.

And fifthly, comprehensively analyzing the similarity of the data information of the target personnel to obtain a personnel relationship set of the target personnel, the multiple associated personnel and the other multiple associated personnel.

And sixthly, carrying out de-duplication processing on the personnel relation set on the condition of the data information of the target personnel to obtain the associated personnel associated with the target personnel.

And seventhly, inquiring track information associated with the associated person from the special database according to the data information of the associated person.

As an example, the executing entity may first associate a plurality of database tables by using the identification card number of the associated person, to obtain a new database table using the identification card number of the associated person as a primary key. The new data table includes the following fields: identification card number, time information, location information, consumption information, related personnel information and related case information. Then, the track information of the target person is drawn through the field information in the new data table.

Eighth, a personnel relation model, a case information model and a case model which are centered on the target personnel are created through the data information, the place information and the case information of the plurality of associated personnel.

And ninth, carrying out safety index comprehensive data analysis according to the personnel relationship model, the case information model and the place model and the track information of the target personnel to obtain a safety index comprehensive data analysis result.

As an example, the execution subject may first assign a first weight to the personnel relationship model, a second weight to the case information model, a third weight to the location information model, and a fourth weight to the target personnel trajectory information. And then, obtaining a safety index comprehensive data analysis result through weighting calculation.

And tenth, setting early warning values for the target personnel, the multiple associated personnel and the other multiple associated personnel according to the comprehensive data analysis result of the safety index. Wherein, the early warning value may be 3. For example, if one associated person is associated with at least 3 target persons, target places and case information at the same time, the associated person is warned.

As an example, the execution subject may set an early warning value for a person who is equal to or greater than the safety index integrated data analysis result. Wherein, the analysis result of the safety index comprehensive data can be 0.8.

And eleventh, early warning is carried out on the personnel exceeding the early warning value, and a relevant police office is reminded to monitor the personnel exceeding the early warning value.

and step one, acquiring the time-space information data of the target personnel. The above-mentioned space-time information data may be time information data and space information data of the target person.

And a second step of determining current track data of the target person according to the space-time data of the target person, wherein the current track data comprises at least one track point.

And thirdly, determining the historical track data of the target personnel according to the historical space-time data of the target personnel.

As an example, the implementation is the same as the implementation of the second step, and will not be described here again.

Fourth, for the target personnel, comparing the similarity between the current track data and the historical track data of the target personnel to obtain a similarity comparison result.

And fifthly, determining whether the current track data of the target person is abnormal track data or not according to the similarity comparison result.

As an example, the execution subject may first determine the similarity of the current trajectory data of the target person and the daily trajectory data in the historical trajectory data, respectively. Then, the number of similarity degrees equal to or larger than the first threshold is taken as the number of similar days. And finally, determining the current track data of the target personnel as abnormal track data in response to determining that the number of similar days is smaller than or equal to a second threshold value.

A sixth step of determining whether at least one abnormal track point in the current track data is an aggregation point in response to determining that the current track data is abnormal track data, wherein the aggregation point is obtained by:

and a substep 1, determining the at least one abnormal track point as a collection point set to be predicted.

Sub-step 2, for each to-be-predicted aggregation point in the to-be-predicted aggregation point set, executing the following determining steps:

a first sub-step of determining a weight corresponding to each of at least one person involved in predicting at least one person information involved in a dataset, wherein the person information includes: the frequency of the personnel history participation group event and the accumulated number of the personnel history participation group event.

And a second sub-step of determining the probability that the point to be aggregated is an aggregation point according to the weight.

And a third sub-step of determining the aggregation point to be predicted as an aggregation point in response to determining that the probability is greater than or equal to a preset threshold.

And seventh, responding to the fact that the at least one abnormal track point comprises an aggregation point, and sending out early warning prompt information according to the position information of the aggregation point so as to enable police officers to monitor the aggregation point. Wherein, the early warning prompt information comprises: the location information of the aggregation point and the personnel information participating in the aggregation.

The technical scheme and the related content are taken as an invention point of the embodiment of the disclosure, so that the technical problem three' in the background art is solved, the accuracy of association analysis of the swarm events is low, and the aggregation point cannot be accurately predicted. ". Factors that lead to lower accuracy of association analysis of the population events tend to be as follows: the public security management data has huge data volume, long data processing period and weaker capacity for data association sharing. If the above factors are solved, an increase in the accuracy of the correlation analysis for the crowd events can be achieved. In order to achieve the effect, the service association search model is used for constructing a server cluster and the target object relation model is used for constructing the server cluster, modeling analysis is carried out on the analysis result, the modeling analysis result is obtained, and the processing steps are executed: acquiring space-time information data of the target personnel; determining current track data of the target person according to the space-time data of the target person, wherein the current track data comprises at least one track point; determining historical track data of the target personnel according to the historical space-time data of the target personnel; for the target personnel, performing similarity comparison on the current track data and the historical track data of the target personnel to obtain a similarity comparison result; and determining whether the current track data of the target personnel is abnormal track data or not according to the similarity comparison result. In response to determining that the current track data is abnormal track data, determining whether at least one abnormal track point in the current track data is an aggregation point, wherein the aggregation point is obtained through the following steps: determining the at least one abnormal track point as a collection point set to be predicted; for each to-be-predicted aggregation point in the to-be-predicted aggregation point set, performing the following determination steps: at least one person information related in a data set to be predicted is used for determining a weight corresponding to each person in the at least one related person, wherein the person information comprises: the frequency of the personnel history participation group event and the accumulated times of the personnel history participation group event; determining the probability that the point to be aggregated is an aggregation point according to the weight; and determining the aggregation point to be predicted as an aggregation point in response to determining that the probability is greater than or equal to a preset threshold. Here, when determining whether the latest track point in the obtained abnormal track data is an aggregation point, the attribute information of the target personnel is fully utilized, so that the error judgment on the aggregation point is greatly reduced, and the accuracy of the judgment on the aggregation point is improved. And responding to the determination that the at least one abnormal track point comprises an aggregation point, and sending out early warning prompt information according to the position information of the aggregation point so as to monitor the aggregation point by police officers.

Step 205, visual query and statistical display are performed on the statistical analysis result through the data visual query server cluster and the visual display server cluster.

In some embodiments, the executing entity may perform visual query and statistical display on the statistical analysis result through the data visual query server cluster and the visual display server cluster. The data visual query server cluster can provide general visual comprehensive query basic service for other server clusters, and a user can perform self-defined selection of query conditions in a visual interface according to specific query requirements to perform comprehensive query on public security management data information. Wherein, the querying may include: the method comprises the steps of accurate query, fuzzy query, query organization and query diversification query mode, and the query result is displayed in a chart mode. The data visualization query server cluster includes: the system comprises a unified report management server, a comprehensive query management server, a statistical analysis management server and a statistical result display server. The visual display server cluster establishes various visual tools such as information collision comparison, deep mining, intelligent research and judgment and the like according to public security management data of multiple data sources, and realizes personnel track analysis, background examination and target personnel identity information verification. The visual display server cluster adopts an engine component, establishes comprehensive inquiry and statistical analysis, and establishes visual display of public security topic research and judgment analysis for dynamic management and control of target persons, target places, target articles and group events and risk hidden danger assessment. The visual display server cluster includes: a data content management server and a visual content server.

By way of example, the execution subject may be configured to provide visual graphical presentation of the statistical analysis results and visual graphical presentation of the query results, so that the querying personnel may have a more intuitive understanding of the security management data of the query.

Referring now to fig. 3, a schematic diagram of an electronic device (e.g., electronic device) 300 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 3 is merely an example and should not impose any limitations on the functionality and scope of use of embodiments of the present disclosure.

As shown in fig. 3, the electronic device 300 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various suitable actions and processes in accordance with a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage means 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic apparatus 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.

In general, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 308 including, for example, magnetic tape, hard disk, etc.; and communication means 309. The communication means 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. While fig. 3 shows an electronic device 300 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead. Each block shown in fig. 3 may represent one device or a plurality of devices as needed.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via communications device 309, or from storage device 308, or from ROM 302. The above-described functions defined in the methods of some embodiments of the present disclosure are performed when the computer program is executed by the processing means 301.

It should be noted that, in some embodiments of the present disclosure, the computer readable medium may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, the computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.

In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (Hyper Text Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.

The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: obtaining public security management data for a plurality of data sources; extracting elements from the public security management data through the data source management server to obtain a special service database; analyzing the special service database through the service research and judgment server cluster to obtain an analysis result; constructing a server cluster through the service association retrieval model and constructing the server cluster through the target object relationship, and carrying out modeling analysis on the analysis result to obtain a statistical analysis result; and carrying out visual query and statistical display on the statistical analysis result.

Computer program code for carrying out operations for some embodiments of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a server, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in some embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The described units may also be provided in a processor, for example, described as: a processor includes an acquisition unit, an extraction unit, an analysis unit, a model construction unit, and a generation unit. The names of these units do not constitute a limitation on the unit itself in some cases, and the acquisition unit may also be described as "a unit that acquires peace management data for a plurality of data sources", for example.

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.

The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above technical features, but encompasses other technical features formed by any combination of the above technical features or their equivalents without departing from the spirit of the invention. Such as the above-described features, are mutually substituted with (but not limited to) the features having similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A peace management integrated information system, comprising: the system comprises a service research judging server cluster, a service association retrieval model constructing server cluster, a target object relation model constructing server cluster, a data visual query server cluster and a visual display server cluster, wherein:

the service research and judgment server cluster is respectively connected with the service association retrieval model construction server cluster and the target object relation model construction server cluster in a communication way, and the service research and judgment server cluster is configured to: and performing research analysis on the public security management data, wherein the business research server cluster comprises: the system comprises a data source management server, a data analysis management server, an index calculation model construction server, a topic analysis model construction server and a topic analysis model construction server, wherein:

the data source management server is configured to: the special business database is obtained by processing public security management data of different data sources and extracting keyword data;

the data analysis management server is communicatively coupled to the data source management server, the data analysis management server configured to: the data analysis management server is a server which determines average values and accumulated sums of a plurality of tables corresponding to the associated information through the associated information;

The topic analysis model building server is in communication with the data source management server, the topic analysis model building server configured to: the statistical analysis is carried out on a plurality of data tables in special security service data in the special service database sent by the data source management server, wherein the special analysis model construction server carries out the homonymous analysis on the total alarming amount and the total alarming amount of the distributed vehicles and the homonymous analysis on the special security service and the special security event, the distributed person alarming amount and the homonymous analysis on the distributed person alarming amount and the target area periphery is provided with the distributed vehicles and the distributed person analysis, and the target area periphery is provided with the server for the alarming period analysis;

the topic analysis model building server is in communication with the data source management server, the topic analysis model building server configured to: carrying out statistical analysis on alarm condition data in the special service database sent by the data source management server, wherein the topic analysis model construction server carries out analysis on the total quantity and the same ratio of alarm condition data in the public security management data, the duty ratio, the total quantity and the same ratio of target alarm condition data, and the current week and the last week trend analysis of the alarm condition alarm period, and sends out servers for forward ranking or reverse ranking of the top 5 current weeks and the last week trend analysis of the alarm condition data;

The index calculation model building server is in communication with the data source management server, the index calculation model building server being configured to: carrying out statistical analysis on target persons, target places and target articles in the special business database sent by the data source management server, wherein the index calculation model construction server provides total and same-proportion analysis, total and distribution analysis of target persons and total and distribution analysis of target places through data information in public security management, and establishes a server for ranking the positive sequence or the reverse sequence times of important articles sent by each sending-out security inspection;

the service association search model building server cluster is respectively in communication connection with the data visual query server cluster and the visual display server cluster, wherein the service association search model building server cluster is configured to: constructing an associated retrieval model for public security management data, and providing associated retrieval data for the data visual query server cluster and the visual display server cluster;

the target object relation model building server cluster is respectively in communication connection with the data visual query server cluster and the visual display server cluster, wherein the target object relation model building server cluster is configured to: building a relational network model for the public security management data and providing relational data for the data visualization query server cluster and the visualization presentation server cluster, wherein the target object relational model building server cluster is configured to: acquiring space-time information data of a target person, wherein the space-time information data are time information data and space information data of the target person;

Determining current track data of the target person according to the space-time data of the target person, wherein the current track data comprises at least one track point;

according to the historical space-time data of the target personnel, determining historical track data of the target personnel;

for the target personnel, carrying out similarity comparison on the current track data and the historical track data of the target personnel to obtain a similarity comparison result;

determining whether the current track data of the target person is abnormal track data or not according to the similarity comparison result;

in response to determining that the current track data is abnormal track data, determining whether at least one abnormal track point in the current track data is an aggregation point, wherein the aggregation point is obtained through the following steps:

determining the at least one abnormal track point as a collection point set to be predicted;

for each to-be-predicted aggregation point in the to-be-predicted aggregation point set, performing the following determining steps:

according to at least one personnel information related in a collection point set to be predicted, determining a weight corresponding to each personnel in the at least one related personnel, wherein the personnel information comprises: the frequency of the personnel history participation group event and the accumulated times of the personnel history participation group event;

Determining the probability that the aggregation point to be predicted is an aggregation point according to the weight;

determining the aggregation point to be predicted as an aggregation point in response to determining that the probability is greater than or equal to a preset threshold;

responding to the determination that the at least one abnormal track point comprises an aggregation point, and sending out early warning prompt information according to the position information of the aggregation point so as to monitor the aggregation point by police officers;

the data visualization query server cluster is configured to: constructing a server cluster according to the business association retrieval model, constructing association retrieval data and relationship data sent by the server cluster according to the target object relationship model, and displaying visual comprehensive query results of the association retrieval data and the relationship data, wherein the data visual query server cluster is a server cluster which displays query results in a graphical visual mode through a received query request of a query person, the query request is a query request of a specific place name, and the query result is a result of a topological relationship network which is centered on the place name and is composed of case information, place information and personnel information related to the place name;

The visual presentation server cluster is configured to: and constructing a server cluster according to the service association retrieval model, constructing association retrieval data and relationship data sent by the server cluster according to the target object relationship model, and visually displaying the association retrieval data and the relationship data.

2. The peace management integrated information system of claim 1, wherein the business-related retrieval model builds a server cluster comprising: case information associated search model construction server, personnel information associated search model construction server, warning information associated search model construction server, wherein:

the case information association retrieval model construction server is configured to: extracting keywords of law enforcement and case handling types and properties in the special business database, and performing model training on the keywords to obtain analysis results;

the person information association retrieval model construction server is configured to: extracting event keywords related to security management types from the special service database, and performing model training on the keywords to obtain analysis results;

the alert information associated retrieval model construction server is configured to: and extracting the warning condition description keywords related to the special service database, and performing model training according to the warning condition keywords to obtain an analysis result.

3. The peace management integrated information system of claim 1, wherein the target object relationship model builds a server cluster comprising: the system comprises a target personnel relationship network model construction server, a case information relationship network model construction server, a target place relationship network model construction server, a group event relationship network model construction server, a space-time analysis relationship network model construction server and a track analysis network model construction server, wherein:

the target person relationship network model building server is configured to: generating a target personnel relationship analysis result through personal information inquiry, and checking information of the associated case and the associated place according to the target personnel relationship analysis result;

the case information relationship network model building server is configured to: generating a case information relation analysis result through case information inquiry, and checking data information of target personnel and target places associated with the case information according to the case information relation analysis result;

the target site relationship network model building server is configured to: generating a target place relation analysis result through target place information inquiry, and checking information of target personnel associated with the target place according to the target place relation analysis result;

The social event relationship network model building server is configured to: generating a crowd event relation analysis result through personal information inquiry, and checking information of target personnel and associated crowd organizations associated with target crowd event according to the crowd event relation analysis result;

the spatiotemporal analysis relationship network model building server is configured to: generating a space-time analysis relation result by inquiring the place and the case information controlled by public security, and checking the related case information and the information of target personnel according to the space-time analysis relation result;

the trajectory analysis network model building server is configured to: track analysis results are generated by constructing personal information queries.

4. The peace management integrated information system of claim 1, wherein the data visualization queries a server cluster comprising: the system comprises a unified report management server, a comprehensive query management server, a statistical analysis management server and a statistical result display server, wherein,

the unified report management server is configured to: the method comprises the steps of sending a fixed report or a flexible report to each level of organization departments to be filled by the organization departments of each level;

The integrated query management server is configured to: providing query result display for public security management data of different data sources, research and judgment analysis results sent by the business research and judgment server cluster, analysis results sent by the business association retrieval model construction server cluster and analysis results sent by the target object relation model construction server cluster through a unified interface;

the statistical analysis management server is configured to: through a unified interface, multidimensional statistical analysis is carried out on public security management data of different data sources, the research analysis results sent by the business research server cluster, the analysis results sent by the business association retrieval model construction server cluster and the analysis results sent by the target object relation model construction server cluster;

the statistics presentation server is configured to: and through a unified interface, performing visual statistical result display on the public security management data of different data sources, the research analysis results sent by the business research server cluster, the analysis results sent by the business association search model building server cluster and the analysis results sent by the target object relation model building server cluster.

5. The peace management integrated information system of claim 1, wherein the visual presentation server cluster includes: a data content management server and a visual content server, wherein:

the data content management server is configured to: supporting to call the data table to the data center and displaying the visual content of the called data table;

the visual content server is configured to: the visualization template is managed.

6. A visual presentation method for the public security management integrated information system of one of claims 1 to 5, comprising:

obtaining public security management data for a plurality of data sources;

extracting elements from the public security management data through a data source management server in the service research and judgment server cluster to obtain a special service database;

performing research analysis on the special service database through the service research server cluster to obtain a research result;

constructing a server cluster through the service association retrieval model and constructing the server cluster through the target object relation model, and carrying out modeling analysis on the research result to obtain a modeling analysis result;

and performing visual query and statistical display on the analysis result through the data visual query server cluster and the visual display server cluster.

7. The method of claim 6, wherein the constructing the server cluster by the business association search model and the target object relation model, performing modeling analysis on the research result to obtain a modeling analysis result, comprises:

acquiring data information of a target personnel database in the special service database;

obtaining track information of a target person according to data information of the target person, wherein the track information comprises: case information related to the target person, consumption behavior of the target person and place information passed by the target person;

inquiring a plurality of cases and a plurality of associated persons which are associated with the cases or relatives of the target person from the special business database through the data information of the target person;

in response to determining that the plurality of associated persons are associated with other target persons, recursively querying other plurality of associated persons having case associations and venue associations with the other target persons, respectively, subject to the other target persons;

performing similarity comprehensive analysis on the data information of the target personnel to obtain a personnel relationship set of the target personnel, the multiple associated personnel and the other multiple associated personnel;

Performing deduplication processing on the personnel relationship set under the condition of the data information of the target personnel to obtain associated personnel associated with the target personnel;

inquiring track information associated with the associated person from the special service database according to the data information of the associated person;

creating a personnel relationship model, a case information model and a place model which take the target personnel as the center through the data information, the place information and the case information of the multiple associated personnel;

carrying out safety index comprehensive data analysis according to the personnel relationship model, the case information model and the place model and the track information of the target personnel to obtain a safety index comprehensive data analysis result;

setting early warning values for the target personnel, the multiple associated personnel and the other multiple associated personnel according to the comprehensive data analysis result of the safety index;

and carrying out early warning on the personnel exceeding the early warning value, and reminding a relevant police office to monitor the personnel exceeding the early warning value.

8. An electronic device, comprising:

one or more processors;

a storage device having one or more programs stored thereon,

When executed by the one or more processors, causes the one or more processors to implement the method of any of claims 6-7.

9. A computer readable medium having stored thereon a computer program, wherein the program when executed by a processor implements the method of any of claims 6-7.