CN112380264A - Policy analysis and matching method and device based on personal full life cycle - Google Patents
Policy analysis and matching method and device based on personal full life cycle Download PDFInfo
- Publication number
- CN112380264A CN112380264A CN202011321571.7A CN202011321571A CN112380264A CN 112380264 A CN112380264 A CN 112380264A CN 202011321571 A CN202011321571 A CN 202011321571A CN 112380264 A CN112380264 A CN 112380264A
- Authority
- CN
- China
- Prior art keywords
- policy
- personal
- matching
- policies
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000004458 analytical method Methods 0.000 title claims description 26
- 238000011161 development Methods 0.000 claims abstract description 9
- 230000009286 beneficial effect Effects 0.000 claims abstract description 7
- 238000004590 computer program Methods 0.000 claims description 6
- 238000013461 design Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000012552 review Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2457—Query processing with adaptation to user needs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/211—Schema design and management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
Abstract
The invention relates to a method and a device for analyzing and matching policies based on a personal full life cycle, which comprises a first step of collecting and analyzing policies and items which are beneficial to personal development and storing the policies and items in a personal policy database; analyzing the policy information in the personal policy database, analyzing personal indexes related in the policy information, extracting and summarizing to form a matching index database; step two, the individual user registers on the information platform, the information platform grasps the comprehensive information of the individual user, and automatically configures individual matching indexes for the individual user according to the matching index library; step three, automatically forming a personal policy matching model according to the policy label and the personal matching index; and forming a personal exclusive policy through a personal policy matching model based on a policy matching algorithm. The invention realizes the 'one-stop and barrier-free' direct communication of the policy to the individual, and is beneficial to solving the problems of unknown personal policy, unknown notification, uncontrollable flow, high acquisition cost and the like.
Description
Technical Field
The invention relates to a policy analysis and matching method and device based on a personal full life cycle, and belongs to the technical field of computers.
Background
Because the policies are distributed scattered due to different types, different release times and different management departments, a large amount of time and energy are needed to search policy sources, verify the timeliness of the policies, evaluate the declaration feasibility and the like, so that various innovation bodies are not facilitated to timely and comprehensively know policy information, the policies meeting self declaration are not conveniently screened from massive policies, and project planning and declaration preparation cannot be fully and effectively made. Therefore, how to screen out the required content from the massive data has become an important research direction in the information technology processing field.
Currently, policy matching systems for enterprises in various cities are emerging continuously, and the traditional 'enterprise policy finding' is developed into 'policy finding enterprise', but a method for analyzing and matching policies for individuals facing to objects is lacked.
Research shows that most of the policy matching systems on the market are for enterprises, and today with high development of the internet, people have ever-increasing attention to national policies, and the policy matching systems on the market are difficult to meet the requirements of individuals on the policies.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a policy analysis and matching method based on the personal full life cycle, which aims to help an individual user to match out a policy of interest quickly and accurately and effectively solve the problem that the existing policy matching system is difficult to meet the requirements of the individual on the policy.
The technical scheme of the invention is as follows:
a method for analyzing and matching policies based on a full life cycle of a person comprises the following steps:
firstly, acquiring and analyzing policies, acquiring the policies by using a policy big data platform on line, and analyzing the policies acquired by the big data platform by a personal policy professional on line, selecting relevant policies suitable for individuals from the policies, adding classification labels to the personal policies, finally analyzing the policies and items beneficial to individual development, storing the policies and items in an individual policy database, and simultaneously extracting and releasing policy items capable of being declared by the individuals;
analyzing the policy information in the personal policy database, analyzing personal indexes related in the policy information, extracting and summarizing to form a matching index database;
secondly, personal information is collected, the personal user registers on the information platform, the information platform grasps the comprehensive information of the personal user, and personal matching indexes are automatically configured for the personal user according to a matching index library;
step three, automatically forming a personal policy matching model according to the policy label in the step one and the personal matching index in the step two; and forming a personal exclusive policy through a personal policy matching model based on a policy matching algorithm.
Preferably, in the step one, the policy is collected by using a policy big data platform on line, which is to collect policies issued by four government departments of the country, province, city and district. The design has the advantages that various policies are complicated, some policies are issued by government departments, some policies are issued by political party organizations, some policies are issued by other social administration groups, only policy information issued by four-level government departments is collected, the collection amount of policies irrelevant to individuals is reduced, and meanwhile the accuracy of the personal policy database is improved.
Preferably, in step two, the comprehensive information of the individual user includes name, age, sex, educational experience, work experience, industry, professional planning and development vision. The design has the advantage that the matching degree of subsequent personal-specific policies can be improved by comprehensively collecting personal user information including but not limited to the information.
A device for analyzing and matching policies based on personal full life cycle comprises a policy acquisition module, a policy analysis module, a personal information collection module, a personal index configuration module and a personal policy matching analysis module;
the policy acquisition module acquires relevant policies and sends the policies to the policy analysis module, the policy analysis module analyzes the personal policies, and classification labels are added to the personal policies;
the personal information collection module collects comprehensive information of the individual user and configures individual matching indexes for the individual user through the individual index configuration module;
and the personal policy matching analysis module forms a personal policy matching model for the personal user through the personal matching index and the policy classification label, and forms a personal exclusive policy according to a policy matching algorithm.
A server, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
when executed by the one or more processors, cause the one or more processors to implement the above-described method for personal full-lifecycle based policy resolution and matching.
A computer-readable medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the method for personal full-lifecycle based policy resolution and matching as described above.
The invention has the technical characteristics and beneficial effects that:
the method and the device for analyzing and matching the policy based on the personal full life cycle can design key matching indexes according to big policy data and form a personal policy library and a personal index library, so that scientific and comprehensive qualitative evaluation is performed on the development of individuals according to basic data of the individuals in the aspects of native place, academic calendar, occupation, special population and the like, policy reference is provided for the individuals, the requirements of the individuals on comprehensively developing and promoting the policy are met in a personalized manner, the policy 'one-stop type and no obstacle' is directly communicated with the individuals, and the problems that the personal policy is unknown, the notification is unknown, the flow is not mastered, the acquisition cost is high and the like are solved.
Drawings
FIG. 1 is a block diagram of a personal full lifecycle based policy resolution and matching system in accordance with the present invention;
FIG. 2 is a schematic flow chart of a personal full-life-cycle based policy resolution and matching system according to the present invention;
FIG. 3 is a schematic flow chart of a policy collecting and analyzing device according to the present invention;
FIG. 4 is a schematic flow chart of an index design apparatus for a key stage of a personal full life cycle according to the present invention;
FIG. 5 is a flowchart illustrating a method for generating a personal policy match according to the present invention.
Detailed Description
The present invention will be further described by way of examples, but not limited thereto, with reference to the accompanying drawings.
Example 1:
the embodiment provides a policy parsing and matching method based on a personal full life cycle, which comprises the following steps:
firstly, acquiring and analyzing policies, acquiring the policies by using a policy big data platform on line, and analyzing the policies acquired by the big data platform by a personal policy professional on line, selecting relevant policies suitable for individuals from the policies, adding classification labels to the personal policies, finally analyzing the policies and items beneficial to individual development, storing the policies and items in an individual policy database, and simultaneously extracting and releasing policy items capable of being declared by the individuals;
analyzing the policy information in the personal policy database, analyzing personal indexes related in the policy information, extracting and summarizing to form a matching index database;
secondly, personal information is collected, the personal user registers on the information platform, the information platform grasps the comprehensive information of the personal user, and personal matching indexes are automatically configured for the personal user according to a matching index library;
step three, automatically forming a personal policy matching model according to the policy label in the step one and the personal matching index in the step two; and forming a personal exclusive policy through a personal policy matching model based on a policy matching algorithm.
In the first step, the policy is collected by using a policy big data platform on line, which is to collect the policies issued by the state, province, city and district four-level government departments. The design has the advantages that various policies are complicated, some policies are issued by government departments, some policies are issued by political parties, some policies are issued by other social administration groups, only policy information issued by four-level government departments is collected, the collection amount of policies irrelevant to individuals is reduced, and meanwhile, the accuracy of the personal policy database is improved.
In step two, the comprehensive information of the individual user includes name, age, gender, educational experience, work experience, employment industry, professional planning and development vision. The design has the advantage that the matching degree of subsequent personal exclusive policies can be improved by comprehensively collecting the personal user information including but not limited to the information.
Specifically, as shown in fig. 2, the basic flow chart of the method, wherein, step 101: collecting related policies through a policy big data platform;
step 102-step 104: after the policies are collected, relevant policy experts review and analyze the policies, screen various policies suitable for various stages of individuals, add various matching labels to the policies, and extract and release policy items capable of being declared by the individuals;
step 105: registering an individual user;
step 106-step 107: after the individual user is successfully registered, collecting basic information of the individual user, and automatically configuring individual matching indexes for the individual user;
step 108-step 109: and forming a personal exclusive policy through a policy matching analysis model based on a policy matching algorithm.
As shown in fig. 3, the process diagram of policy collection and analysis in the first step includes the following steps:
102, performing content and form review on the acquired policy, perfecting and issuing the policy;
103, analyzing by related policy experts according to the policies issued in the step 102, screening various policies suitable for various stages of the individual, and adding various matching labels for the policies;
and 104-105, extracting a reportable policy item according to the analysis result of the expert in the step 103, and entering a personal policy library after evaluation.
As shown in fig. 4, the flow chart of the personal matching index in the second step includes the following steps:
step 101-step 102, analyzing personal indexes related in policy information, extracting and summarizing to form a matching index library;
103, registering the individual user;
and 104-106, collecting user basic information after the personal user is successfully registered, and automatically configuring and generating a personal matching index according to a matching index library.
As shown in fig. 5, the flow chart of forming the personal-specific policy in step three includes the following steps:
step 101-step 103, automatically forming a personal policy matching model according to the policy label and the personal matching index;
step 104-step 105, forming a personal exclusive policy based on a policy matching algorithm through the policy matching model formed in step 101-step 103.
Example 2:
a device for analyzing and matching policies based on personal full life cycle comprises a policy acquisition module, a policy analysis module, a personal information collection module, a personal index configuration module and a personal policy matching analysis module;
the policy acquisition module acquires relevant policies and sends the policies to the policy analysis module, the policy analysis module analyzes the personal policies, and classification labels are added to the personal policies;
the personal information collection module collects comprehensive information of the individual user and configures individual matching indexes for the individual user through the individual index configuration module;
and the personal policy matching analysis module forms a personal policy matching model for the personal user through the personal matching index and the policy classification label, and forms a personal exclusive policy according to a policy matching algorithm.
As shown in fig. 1, the policy collection module collects the relevant policies by using a policy big data platform through a big data technology;
the policy analysis module belongs to a product center of the system, and is reviewed and analyzed by relevant policy experts, so that various policies suitable for various stages of an individual are effectively screened out, various matching labels are added to the policies, and finally, the policies and projects which are beneficial to the individual are reasonably analyzed;
the personal policy matching analysis model is a core module of the system, and forms a personal exclusive policy based on a policy matching algorithm through the policy matching analysis model.
Example 3:
a server, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
when executed by the one or more processors, cause the one or more processors to implement the method for personal full-lifecycle based policy resolution and matching of embodiment 1.
Example 4:
a computer-readable medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the method for personal full-life based policy resolution and matching of embodiment 1.
The above description is only for the specific embodiments of the present invention, and the protection scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention disclosed herein should be covered within the protection scope of the present invention.
Claims (6)
1. A method for analyzing and matching policies based on a full life cycle of a person is characterized by comprising the following steps:
firstly, policy collection and analysis, namely collecting policies by using a policy big data platform on line, and organizing personal policy experts to analyze the policies collected by the big data platform off line, selecting relevant policies suitable for individuals from the policies, adding classification labels to the personal policies, finally analyzing the policies and items beneficial to personal development, storing the policies and items in a personal policy database, and extracting and releasing policy items capable of being declared by individuals;
analyzing the policy information in the personal policy database, analyzing personal indexes related in the policy information, extracting and summarizing to form a matching index database;
secondly, personal information is collected, the personal user registers on the information platform, the information platform grasps the comprehensive information of the personal user, and personal matching indexes are automatically configured for the personal user according to a matching index library;
step three, automatically forming a personal policy matching model according to the policy label in the step one and the personal matching index in the step two; and forming a personal exclusive policy through a personal policy matching model based on a policy matching algorithm.
2. The method for personal full-life-cycle-based policy resolution and matching according to claim 1, wherein in the step one, the policy is collected by using a policy big data platform on line, and the policy is collected from government departments of the state, province, city, and district four levels.
3. The method for personal full-life-cycle based policy resolution and matching according to claim 1, wherein in step two, the comprehensive information of the individual user comprises name, age, gender, educational experience, work experience, industry, occupational planning and development vision.
4. A device for analyzing and matching policies based on personal full life cycle comprises a policy acquisition module, a policy analysis module, a personal information collection module, a personal index configuration module and a personal policy matching analysis module;
the policy acquisition module is used for acquiring relevant policies and sending the policies to the policy analysis module, the policy analysis module is used for analyzing the personal policies and adding classification labels to the personal policies;
the personal information collection module collects comprehensive information of the individual user and configures individual matching indexes for the individual user through the individual index configuration module;
and the personal policy matching analysis module forms a personal policy matching model for the personal user through the personal matching index and the policy classification label, and forms a personal exclusive policy according to a policy matching algorithm.
5. A server, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
when executed by the one or more processors, cause the one or more processors to implement the method for personal full-lifecycle based policy resolution and matching of claim 1.
6. A computer-readable medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the method for personal full-life based policy resolution and matching of claim 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011321571.7A CN112380264A (en) | 2020-11-23 | 2020-11-23 | Policy analysis and matching method and device based on personal full life cycle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011321571.7A CN112380264A (en) | 2020-11-23 | 2020-11-23 | Policy analysis and matching method and device based on personal full life cycle |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112380264A true CN112380264A (en) | 2021-02-19 |
Family
ID=74588819
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011321571.7A Pending CN112380264A (en) | 2020-11-23 | 2020-11-23 | Policy analysis and matching method and device based on personal full life cycle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112380264A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113592368A (en) * | 2021-09-29 | 2021-11-02 | 深圳市指南针医疗科技有限公司 | Index data extraction method, device, equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109408683A (en) * | 2018-10-31 | 2019-03-01 | 广州高企云信息科技有限公司 | A kind of policy intelligent Matching system and method |
| CN110457696A (en) * | 2019-07-31 | 2019-11-15 | 福州数据技术研究院有限公司 | A kind of talent towards file data and policy intelligent Matching system and method |
| CN111159630A (en) * | 2019-12-31 | 2020-05-15 | 科技谷（厦门）信息技术有限公司 | Park policy matching and evaluating method based on multi-standard decision model |
| CN111680073A (en) * | 2020-06-11 | 2020-09-18 | 天元大数据信用管理有限公司 | Financial service platform policy information recommendation method based on user data |
-
2020
- 2020-11-23 CN CN202011321571.7A patent/CN112380264A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109408683A (en) * | 2018-10-31 | 2019-03-01 | 广州高企云信息科技有限公司 | A kind of policy intelligent Matching system and method |
| CN110457696A (en) * | 2019-07-31 | 2019-11-15 | 福州数据技术研究院有限公司 | A kind of talent towards file data and policy intelligent Matching system and method |
| CN111159630A (en) * | 2019-12-31 | 2020-05-15 | 科技谷（厦门）信息技术有限公司 | Park policy matching and evaluating method based on multi-standard decision model |
| CN111680073A (en) * | 2020-06-11 | 2020-09-18 | 天元大数据信用管理有限公司 | Financial service platform policy information recommendation method based on user data |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113592368A (en) * | 2021-09-29 | 2021-11-02 | 深圳市指南针医疗科技有限公司 | Index data extraction method, device, equipment and storage medium |
| CN113592368B (en) * | 2021-09-29 | 2021-12-28 | 深圳市指南针医疗科技有限公司 | Index data extraction method, device, equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112182246B (en) | Method, system, medium, and application for creating an enterprise representation through big data analysis | |
| CN110851667B (en) | Integration analysis method and tool for large amount of data of multiple sources | |
| CN110119395B (en) | Method for realizing association processing of data standard and data quality based on metadata in big data management | |
| CN111324602A (en) | Method for realizing financial big data oriented analysis visualization | |
| CN111611458A (en) | Method for realizing system data architecture combing based on metadata and data analysis technology in big data management | |
| CN110751361B (en) | Bank demand entry level management method and system | |
| Irudeen et al. | Big data solution for Sri Lankan development: A case study from travel and tourism | |
| CN111125068A (en) | Metadata management method and system | |
| CN110109908B (en) | Analysis system and method for mining potential relationship of person based on social basic information | |
| Daskalaki et al. | Instance matching benchmarks in the era of linked data | |
| CN111553137B (en) | Report generation method and device, storage medium and computer equipment | |
| CN112836018A (en) | Method and device for processing emergency plan | |
| CN112380264A (en) | Policy analysis and matching method and device based on personal full life cycle | |
| Talha et al. | Towards a powerful solution for data accuracy assessment in the big data context | |
| Goasdoué et al. | An Evaluation Framework For Data Quality Tools. | |
| CN114722789B (en) | Data report integrating method, device, electronic equipment and storage medium | |
| CN110019237B (en) | System and method for analyzing criminal whereabouts based on map | |
| Ping | An empirical study of collection assessment based on the quality–utility–value theory | |
| CN113157978B (en) | Data label establishing method and device | |
| Goel et al. | Data governance for managing data quality in process mining | |
| Asroni et al. | Dashboard-based Alumni Tracer Study Report Using Normalized Data Store Architecture | |
| CN112418260A (en) | Model training method, information prompting method, device, equipment and medium | |
| Futia et al. | ContrattiPubblici. org, a semantic knowledge graph on public procurement information | |
| Elias et al. | Validating the IS-Impact model: two exploratory case studies in China and Malaysia | |
| CN113868322B (en) | Semantic structure analysis method, device and equipment, virtualization system and medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210219 |
|
| RJ01 | Rejection of invention patent application after publication |