CN111680073A - Financial service platform policy information recommendation method based on user data - Google Patents
Financial service platform policy information recommendation method based on user data Download PDFInfo
- Publication number
- CN111680073A CN111680073A CN202010529610.6A CN202010529610A CN111680073A CN 111680073 A CN111680073 A CN 111680073A CN 202010529610 A CN202010529610 A CN 202010529610A CN 111680073 A CN111680073 A CN 111680073A
- Authority
- CN
- China
- Prior art keywords
- data
- user
- policy information
- analyzing
- indexes
- 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
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
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
-
- 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
- G06F16/248—Presentation of query results
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Probability & Statistics with Applications (AREA)
- Business, Economics & Management (AREA)
- Software Systems (AREA)
- Mathematical Physics (AREA)
- Fuzzy Systems (AREA)
- Accounting & Taxation (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Finance (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Technology Law (AREA)
- General Business, Economics & Management (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention provides a financial service platform policy information recommendation method based on user data, belongs to the technical field of big data, and matches relevant policy data for a user according to a user portrait. The financial related policies and news information published on the website are stored through manual or automatic acquisition of a big data platform, and are subjected to label classification, and the classified labels are matched with the user portrait. For an organization or an enterprise with huge data volume, the efficiency of the financial service platform can be improved by using the scheme.
Description
Technical Field
The invention relates to a big data technology, in particular to a financial service platform policy information recommendation method based on user data.
Background
Due to the rapid development of the big data era, the data volume required to be maintained or analyzed by a plurality of organizations and enterprises is huge continuously, the financial service industry needs to accurately and directionally analyze images of users, and the traditional backward data use cannot adapt to the current big data volume. Most data are stored in the database and cannot be effectively utilized, and the extraction of relevant data is time-consuming and labor-consuming. At present, most financial service platforms require users to search for financial related policies and related news information suitable for the users from all places, and the financial service platforms are time-consuming and labor-consuming.
In addition, the user image has certain limitations, such as missing of partial data, timeliness of data, and the like.
Disclosure of Invention
In order to solve the technical problems, the invention provides a financial service platform policy information recommendation method based on user data, so that the efficiency of a financial service platform is improved.
The technical scheme of the invention is as follows:
a financial service platform policy information personalized recommendation method based on user data,
comprises that
A creates a user representation using the user big data,
b collecting and labeling the classification policy information,
c timeliness of policy information.
The financial related policies and news information published on the website are stored through manual or automatic acquisition of a big data platform, and are subjected to label classification, and the classified labels are matched with the user pictures.
Further, in the above-mentioned case,
and creating a user image by using the user big data, namely collecting and sorting the user data and analyzing the user data.
The collecting and labeling of classification policy information is characterized by collecting and labeling classification policy information.
The timeliness of the policy information is characterized by timeliness of the policy information.
The collecting collates user data, which is characterized by acquiring data from various government departments.
The user data analysis is characterized in that the user data analysis is generalized into various indexes related to finance, and a user portrait is created according to the indexes
Further, in the above-mentioned case,
data related to finance is collected, primary processing and screening are carried out after the data are obtained, and correlation and data loss rate statistics of all departments are carried out so as to analyze the data in the following process.
Further, in the above-mentioned case,
and analyzing the user data, namely analyzing and summarizing the user data into various indexes related to finance, and creating the user portrait according to the indexes.
Further, in the above-mentioned case,
analyzing the existing data and establishing the existing data on the basis of setting indexes for a user; processing data into various indexes by analyzing various relevant data of the user;
in the process of data analysis, the data missing situation of each special user is counted at the same time.
Further, in the above-mentioned case,
after analyzing the data, obtaining various indexes of the user and the missing rate of the data; when the non-set data loss rate is lower than 12%, the user portrait has higher accuracy; according to the indexes obtained by data analysis, the characteristics of policy information are combined to portray the user.
Further, in the above-mentioned case,
the collect and tag classification policy information, i.e., collect and tag classification policy information.
The method is provided with two modes of manual maintenance and platform collection, and stores the collected policy information in the form of characters or pictures.
And (4) label classification: analyzing characters and semantics, extracting policy information keywords, and marking 10-15 labels aiming at different user groups for different categories.
Further, in the above-mentioned case,
policy information recommendation: having user image and policy information classification label, matching the user and the collected policy information; according to the index conditions of the users, the importance degree of the indexes and the timeliness of the policy information, the policy information helpful for the users is screened out, and the policy information is ranked and recommended to the users according to the possibility.
The invention has the advantages that
1. The user portrait is created, so that accurate policy information recommendation can be performed on different users, and the efficiency of solving the self requirements of the users is improved.
2. The platform can count the policy information recommendation history so as to improve the collection method of the policy information.
3. The policy information recommendation is performed according to the user image, so that the operation efficiency of the financial service platform can be improved.
Drawings
FIG. 1 is a schematic workflow diagram of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer and more complete, the technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention, and based on the embodiments of the present invention, all other embodiments obtained by a person of ordinary skill in the art without creative efforts belong to the scope of the present invention.
If the user portrait can be created by using big data in advance and the relevant policies and news information of finance of each channel are stored and centralized, timely and applicable information can be accurately provided for the user, and the operation efficiency of the financial service platform is improved.
The invention provides a financial service platform policy information personalized recommendation method based on user data, which comprises the steps of user portrayal, acquisition of related policy information data, classification of policy information labels and the like, and needs a big data platform to support realization. The user representation can be applied to various industries, and is created for each user according to user data from government data and the like and combined conditions, so that the user representation can be matched with relevant policy data according to the user representation. The financial related policies and news information published on the website are stored and classified by manual or automatic acquisition of a big data platform, and the meaning of the method is that the classified labels are matched with the user portrait. For an organization or an enterprise with huge data volume, the efficiency of the financial service platform can be improved by using the scheme.
The invention is mainly divided into two parts on the whole, and creates a user portrait and policy information personalized recommendation.
Creating a user representation: the method can be divided into the following steps: 1) collecting data, 2) analyzing the data, 3) constructing a representation.
Wherein the content of the first and second substances,
1) collecting data
Government data related to finance mainly come from government departments such as public security departments, industrial and commercial departments, tax departments and the like. The data of each government department has certain difference in standard, and after the data are obtained, preliminary processing and screening are carried out, such as data association of each department, data missing rate statistics and the like, so that the data can be analyzed subsequently.
2) Analyzing data: existing data are analyzed and established on the basis of various indexes set by a user. For example, the income ability and the fixed assets (debt repayment ability) can be classified into strong, general, poor and other indexes according to specific indexes, and the data is processed into each index through the analysis of each relevant data of the user. The missing rate of data affects the integrity of the index, so the missing data condition of each special user is also counted in the data analysis process.
3) Creating a user representation: after the step of analyzing data, we will obtain various indexes of the user and the missing rate of the data. The user representation has higher accuracy only when the non-critical data loss rate is lower than 12%. According to the indexes obtained by data analysis, the characteristics of policy information are combined to portray the user.
Policy information personalized recommendation:
1) collecting policy information: collect relevant policy and news information in finance from channels such as national or local websites. There are two modes of manual maintenance and platform collection. Storing the collected text or picture policy information.
2) The label classification: analyzing the text and semantic meaning and extracting the keywords of policy information. It is labeled with 10-15 labels for different categories of different user groups.
3) The policy information recommendation function: having the user image and the policy information classification label, it can match the user and the collected policy information. According to the condition of each index of the user, the importance degree of the index and the timeliness of the policy information, the policy information which is more likely to be helpful to the user is screened out, and the policy information is ranked and recommended to the user according to the possibility.
The above description is only a preferred embodiment of the present invention, and is only used to illustrate the technical solutions of the present invention, and not to limit the protection scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (10)
1. A financial service platform policy information recommendation method based on user data is characterized in that,
the method comprises the following steps:
a, creating a user portrait by utilizing user big data;
b, collecting and labeling classification policy information;
c, recommending the timeliness of policy information;
the financial related policies and news information published on the website are stored through manual or automatic acquisition of a big data platform, and are subjected to label classification, and the classified labels are matched with the user pictures.
2. The method of claim 1,
and creating a user image by using the user big data, namely collecting and sorting the user data and analyzing the user data.
3. The method of claim 2,
data related to finance is collected, primary processing and screening are carried out after the data are obtained, and correlation and data loss rate statistics of all departments are carried out so as to analyze the data in the following process.
4. The method of claim 2,
and analyzing the user data, namely analyzing and summarizing the user data into various indexes related to finance, and creating the user portrait according to the indexes.
5. The method of claim 4,
analyzing the existing data and establishing the existing data on the basis of setting indexes for a user; processing data into various indexes by analyzing various relevant data of the user;
in the process of data analysis, the data missing situation of each special user is counted at the same time.
6. The method of claim 5,
after analyzing the data, obtaining various indexes of the user and the missing rate of the data; when the non-set data loss rate is lower than 12%, the user portrait has higher accuracy; according to the indexes obtained by data analysis, the characteristics of policy information are combined to portray the user.
7. The method of claim 1,
the collect and tag classification policy information, i.e., collect and tag classification policy information.
8. The method of claim 7,
the method is provided with two modes of manual maintenance and platform collection, and stores the collected policy information in the form of characters or pictures.
9. The method of claim 7,
and (4) label classification: analyzing characters and semantics, extracting policy information keywords, and marking 10-15 labels aiming at different user groups for different categories.
10. The method of claim 1,
the policy information recommendation function: having user image and policy information classification label, matching the user and the collected policy information; according to the index conditions of the users, the importance degree of the indexes and the timeliness of the policy information, the policy information helpful for the users is screened out, and the policy information is ranked and recommended to the users according to the possibility.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010529610.6A CN111680073A (en) | 2020-06-11 | 2020-06-11 | Financial service platform policy information recommendation method based on user data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010529610.6A CN111680073A (en) | 2020-06-11 | 2020-06-11 | Financial service platform policy information recommendation method based on user data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111680073A true CN111680073A (en) | 2020-09-18 |
Family
ID=72454658
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010529610.6A Pending CN111680073A (en) | 2020-06-11 | 2020-06-11 | Financial service platform policy information recommendation method based on user data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111680073A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112380264A (en) * | 2020-11-23 | 2021-02-19 | 政和科技股份有限公司 | Policy analysis and matching method and device based on personal full life cycle |
| CN112380318A (en) * | 2020-11-12 | 2021-02-19 | 中国科学技术大学智慧城市研究院(芜湖) | Enterprise policy matching method based on label similarity |
| CN112651877A (en) * | 2021-01-20 | 2021-04-13 | 天元大数据信用管理有限公司 | Design method of financial comprehensive service platform and financial comprehensive service platform |
| CN112685638A (en) * | 2020-12-30 | 2021-04-20 | 深圳市华傲数据技术有限公司 | Data processing method, device and storage medium |
| CN113379581A (en) * | 2021-08-16 | 2021-09-10 | 迅管(深圳)科技有限公司 | Special service pushing method and system based on user portrait |
| CN113837859A (en) * | 2021-08-25 | 2021-12-24 | 天元大数据信用管理有限公司 | Small and micro enterprise portrait construction method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107818336A (en) * | 2017-10-09 | 2018-03-20 | 中国电子科技集团公司第二十八研究所 | Method and system are recommended in a kind of matching based on city specific crowd and the policy that associates |
| WO2018157818A1 (en) * | 2017-03-02 | 2018-09-07 | 广州市动景计算机科技有限公司 | Method and apparatus for inferring preference of user, terminal device, and storage medium |
| CN110275952A (en) * | 2019-05-08 | 2019-09-24 | 平安科技（深圳）有限公司 | News recommended method, device and medium based on user's short-term interest |
| CN110797124A (en) * | 2019-10-30 | 2020-02-14 | 腾讯科技（深圳）有限公司 | Model multi-terminal collaborative training method, medical risk prediction method and device |
| CN110956303A (en) * | 2019-10-12 | 2020-04-03 | 未鲲(上海)科技服务有限公司 | Information prediction method, device, terminal and readable storage medium |
| CN111159341A (en) * | 2019-12-25 | 2020-05-15 | 中国建设银行股份有限公司 | Information recommendation method and device based on user investment and financing preference |
-
2020
- 2020-06-11 CN CN202010529610.6A patent/CN111680073A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018157818A1 (en) * | 2017-03-02 | 2018-09-07 | 广州市动景计算机科技有限公司 | Method and apparatus for inferring preference of user, terminal device, and storage medium |
| CN107818336A (en) * | 2017-10-09 | 2018-03-20 | 中国电子科技集团公司第二十八研究所 | Method and system are recommended in a kind of matching based on city specific crowd and the policy that associates |
| CN110275952A (en) * | 2019-05-08 | 2019-09-24 | 平安科技（深圳）有限公司 | News recommended method, device and medium based on user's short-term interest |
| CN110956303A (en) * | 2019-10-12 | 2020-04-03 | 未鲲(上海)科技服务有限公司 | Information prediction method, device, terminal and readable storage medium |
| CN110797124A (en) * | 2019-10-30 | 2020-02-14 | 腾讯科技（深圳）有限公司 | Model multi-terminal collaborative training method, medical risk prediction method and device |
| CN111159341A (en) * | 2019-12-25 | 2020-05-15 | 中国建设银行股份有限公司 | Information recommendation method and device based on user investment and financing preference |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112380318A (en) * | 2020-11-12 | 2021-02-19 | 中国科学技术大学智慧城市研究院(芜湖) | Enterprise policy matching method based on label similarity |
| CN112380264A (en) * | 2020-11-23 | 2021-02-19 | 政和科技股份有限公司 | Policy analysis and matching method and device based on personal full life cycle |
| CN112685638A (en) * | 2020-12-30 | 2021-04-20 | 深圳市华傲数据技术有限公司 | Data processing method, device and storage medium |
| CN112651877A (en) * | 2021-01-20 | 2021-04-13 | 天元大数据信用管理有限公司 | Design method of financial comprehensive service platform and financial comprehensive service platform |
| CN113379581A (en) * | 2021-08-16 | 2021-09-10 | 迅管(深圳)科技有限公司 | Special service pushing method and system based on user portrait |
| CN113837859A (en) * | 2021-08-25 | 2021-12-24 | 天元大数据信用管理有限公司 | Small and micro enterprise portrait construction method |
| CN113837859B (en) * | 2021-08-25 | 2024-05-14 | 天元大数据信用管理有限公司 | Image construction method for small and micro enterprises |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111680073A (en) | Financial service platform policy information recommendation method based on user data | |
| CN108572967B (en) | Method and device for creating enterprise portrait | |
| US20170004128A1 (en) | Device and method for analyzing reputation for objects by data mining | |
| US20050182736A1 (en) | Method and apparatus for determining contract attributes based on language patterns | |
| CN112182246B (en) | Method, system, medium, and application for creating an enterprise representation through big data analysis | |
| CN108153729B (en) | Knowledge extraction method for financial field | |
| CN111125343A (en) | Text analysis method and device suitable for human-sentry matching recommendation system | |
| CN115293131B (en) | Data matching method, device, equipment and storage medium | |
| CN111967761A (en) | Monitoring and early warning method and device based on knowledge graph and electronic equipment | |
| CN111882403A (en) | Financial service platform intelligent recommendation method based on user data | |
| CN110880142B (en) | Risk entity acquisition method and device | |
| CN116384889A (en) | Intelligent analysis method for information big data based on natural language processing technology | |
| CN111553137B (en) | Report generation method and device, storage medium and computer equipment | |
| CN114648393A (en) | Data mining method, system and equipment applied to bidding | |
| CN112685564A (en) | Intelligent science and technology policy classification and pushing method and system | |
| CN110544035A (en) | internal control detection method, system and computer readable storage medium | |
| CN110941702A (en) | Retrieval method and device for laws and regulations and laws and readable storage medium | |
| CN115809653A (en) | Intelligent contract auditing method and system | |
| CN114385609A (en) | Label-based government affair event processing system, method, equipment and storage medium | |
| CN111858560B (en) | Financial data automatic testing and monitoring system based on data warehouse | |
| US9165053B2 (en) | Multi-source contextual information item grouping for document analysis | |
| CN111859108A (en) | Public opinion system search word recommendation system | |
| CN114495138A (en) | Intelligent document identification and feature extraction method, device platform and storage medium | |
| AU2021209048A1 (en) | Systems and method for dynamically updating materiality distributions and classifications | |
| CN111125345A (en) | Data application method and device |
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 |