CN112347243A - Enterprise bankruptcy information service method based on big data collection, processing and personalized display pushing - Google Patents

Abstract

The method is an enterprise bankruptcy information service method based on big data collection, processing and display pushing, and relates to the technologies of internet, cloud computing and big data; through big data collection, browsable bankruptcy case related data, bankruptcy debtor related data, bankruptcy professional articles and bankruptcy related public opinion data which are disclosed in the whole network range are collected, user preference data is obtained based on user orders or user behaviors, data is extracted, converted, cleaned and correlated through cloud computing and big data technology, data which are concerned by or customized by a user are generated based on the user preference data, then screening, classifying and composing are carried out through a user interface layer, and finally data display and pushing are carried out through desktop application programs, webpage query, APP, WeChat public numbers, WeChat small programs, mails, short messages and the like, so that comprehensive, quick, high-quality, personalized bankruptcy information data service of thousands of people is completed.

Description

Enterprise bankruptcy information service method based on big data collection, processing and personalized display pushing

[ Abstract of technical characteristics ]

The bankruptcy information service method based on big data collection, processing and display pushing is provided. Through big data collection, browsable bankruptcy case related data, bankruptcy debtor related data, bankruptcy professional articles and bankruptcy related public opinion data which are disclosed in the whole network range are collected. Meanwhile, preference data of the user on bankruptcy data is obtained through a user order or user behaviors. Through cloud computing and big data technology, data are extracted, converted, cleaned and correlated, and data concerned by or customized by a user are generated based on user preference data. And then the user interface layer is used for screening, classifying and typesetting. The data display and push are carried out through a desktop application program, a webpage query, an APP, a WeChat public number, a WeChat applet, a mail, a short message and the like, and then comprehensive, quick, high-quality and personalized bankruptcy information data service of thousands of people is completed.

[ technical field ] A method for producing a semiconductor device

The invention relates to application of technologies such as internet, cloud computing, big data collection, big data storage, big data extraction, conversion and cleaning, data display user interface, data report generation and data pushing in the aspect of enterprise bankruptcy information, in particular to a method for realizing collection, processing and classification of enterprise bankruptcy information to form a data directory report and pushing or displaying data concerned by the enterprise bankruptcy information to a user based on big data collection, processing and display pushing.

[ background of the invention ]

At present, the problem of insufficient informatization exists in the field of bankruptcy, and the information in the field of bankruptcy mainly covers the following aspects.

First, the enterprise is applied for bankruptcy information.

Second, the enterprise on court delivery decides and decides.

And thirdly, announcement information of each stage of the enterprise bankruptcy program, such as investor recruitment announcement, supervisor recruitment announcement, case announcement, creditor conference announcement, pre-reforming announcement, reforming plan draft and the like.

Fourth, the auction information of the property of the bankruptcy enterprise.

Fifth, case of lawsuit related to bankruptcy.

Sixthly, the latest theory and practical research of the bankruptcy boundary progresses.

Seventh, the important legislative development of the bankruptcy law and the related news reports of the major cases.

Currently, major stakeholders and related information needs in the industry of bankruptcy.

Shareholder of bankruptcy enterprise

The method is concerned about the ownership of own shareholder equity after a bankruptcy program, and particularly, the bankruptcy case of a listed company relates to a large number of public shareholders.

Second, the creditor

Refers to a legal person or a natural person who has the right of debt to a bankruptcy enterprise. The creditor enjoys the debt in the bankruptcy program in the situation of being unable to fully settle. In the bankruptcy law, the debt rights are classified into specific property guarantee debt rights, general debt rights, tax debt rights, social insurance debt rights, labor debt rights and the like according to the types of the debt rights, and the information acquisition of the debt rights is important service content of a manager. The creditors can be divided into financial creditors and non-financial creditors according to whether the creditors are financial institutions or not, wherein the financial creditors can be multiple bankruptcy enterprise creditors at the same time, and the need for information is not only limited to information of a single case, but also more systematic data services are often needed.

Third, lawyer

Lawyers engaged in or interested in bankruptcy may participate as managers in cases and also be concerned with the opportunity to provide legal services to bankruptcy enterprise stakeholders, creditor stakeholders, the government where the bankruptcy enterprise is located. Meanwhile, lawyers engaged in civil litigation also need to understand the progress of the labor-breaking procedure and adjust the complaint strategy after the failure of the party involved in the case.

And fourthly, relevant intermediary mechanisms except for the law.

Services related to bankruptcy exist in auditing and evaluation organizations and the like.

Court of five, all levels

Courts in different regions at all levels need to comprehensively acquire relevant information of a bankruptcy method to improve judging capability. The distribution of the bankruptcy cases shows the condition that the provinces in the southeast coastal region are more and the provinces in the inland are less, the trial and error experience of the bankruptcy cases in a plurality of regional courts is less, and the requirement on the relevant information of the actual practice of the bankruptcy method is very urgent.

Sixthly, investors

Bankruptcy asset investment is an important area of investment. The failure of the enterprise does not mean that the enterprise does not have good assets, and the investor can obtain a high yield by investing good-quality failure property. The participation mode of investors can be used as a whole investor to take a complete or partial block of a bankruptcy enterprise, and can also purchase the enterprise assets after clearing. The bankruptcy enterprise investor needs to obtain latest bankruptcy enterprise asset disposal information issued by the bankruptcy manager.

Seventh, poor asset management company

In a broad sense, poor asset management companies belong to the category of investors, but generally, the investment targets of poor asset management companies are mostly bankruptcy debt rights at present, and the investment behaviors are accompanied by policy considerations, which can be listed as a single category of participants, which also have demands on bankruptcy related information.

The prior art has the following ways of acquiring relevant information of bankruptcy:

first, direct access.

The bankruptcy case is one of judicial cases, receives the specifications of the relevant system of judicial disclosure, needs to be announced according to legal regulations, such as bankruptcy acceptance and adjudication, debt right application notice and the like, and announces ways such as newspapers, websites and the like. The related judgment and sanction documents can be inquired on the network. All levels of courts can also release relevant data of bankruptcy trial and judgment and latest practical progress through official channels. For the enterprises on the market, the bankruptcy related matters which have great influence on the enterprise operation and seriously affect the benefits of stockholders need to be disclosed publicly. The latest theoretical research of the bankruptcy method can be obtained through an academic article database, and respective media can be reprinted.

And II, indirect acquisition way.

First, when a business is about to be destroyed, it consults local court, counselor and reports to government organization, and the related information is transmitted orally. Secondly, news stories may cover cases with greater influence.

At present, the rising of self-media represented by WeChat public numbers also provides a new important channel for users to obtain bankruptcy related information. The user can form a WeChat group through a friend circle of people in the industry and all the same industry to push and obtain the latest important information.

The main problems of the acquisition of the related information of the bankruptcy at present are as follows:

firstly, the information acquisition cost is high

Although the bankruptcy case is only used as a professional field of the legal industry, a plurality of key websites have concentrated effective information, the total information is scattered, and users need to search each information source regularly if needing to acquire comprehensive information. Meanwhile, the acquisition modes and terminals of different information sources are different, and the information acquisition cost of a user is improved. At present, many information sources can enable users to passively receive information in a push mode, such as micro-information group push and micro-information public number push, but users often need to passively acquire many irrelevant information, such as advertisements and communication information among other users, and the time cost for the users to acquire effective information is high.

Secondly, information cannot be classified accurately

At present, the classification mode of the bankruptcy information sources is far different from the user requirements, even no classification exists, and the original classification modes of some important bankruptcy information sources are mainly classified according to the theoretical significance of the information, pursue the integrity of logic and are not classified according to the business value of the information and the business development requirements of interest correlators. Meanwhile, each main information source faces nationwide users, and regional classification of information is insufficient. The information concerned by the interest correlators has extremely strong regionality, and the area covered by the concerned key information is gradually reduced from a first-line city to a third-line city according to the area of the interest correlators. In terms of the number of users, the number of three-line and four-line users is an absolute majority, the demand for much information only stays in the peripheral area, and even the interest area of the service is special for the stakeholders who relate to a plurality of provincial areas. The information in the other areas is substantially redundant for these users, which increases the time cost for the users to obtain the information. Besides the requirement of acquiring regional classification information, other data classifications are necessary, such as bankruptcy case relatives, e.g., investors, lawyers, intermediaries, and bad asset management organizations, which are concerned about the size of bankruptcy enterprises. In practice, enterprises with no production and capable of breaking are very common, in recent years, judicial systems have vigorously promoted 'breaking by force', a great part of executives have no property for execution, the situation of procedures for breaking production is difficult to turn, and only enterprises with large scale with large production breaking have great commercial value. Finally, many investors may only be concerned with bankruptcy assets of a particular industry or class.

And thirdly, the information integration capability is poor.

Different bankruptcy information is independent and not related, a user cannot conveniently acquire the information of a plurality of information sources at one time, the function of each piece of information cannot be exerted to the maximum extent, and a joint effect cannot be generated. For example, when a user obtains certain information of one debtor, other information related to the same debtor may appear in different information sources and at different time points, the user cannot obtain all the information at the same time, and cannot know case progress and time line information from various angles, and manually associating the information is a time-consuming and labor-consuming process which cannot guarantee quality.

Present solutions to these problems and problems

One, website technology

The website technology refers to a website program realized by technologies such as Html, Html5, CSS, Javascript, Java, PHP, NET and the like, adopts a B/S architecture, is deployed by a server at a server side, can be accessed by an IP address and a domain name, and can allow a user to access and browse query information. The technology can provide comprehensive information browsing and query, is cross-platform and is not limited and restricted by an operating system. However, this technique is problematic in that users are inefficient in finding and acquiring information that they need. This is because, first, the user must browse information extensively, select the information that the user wants from it, and then copy and record, and if the format is not the format that the user wants finally, then the user must also perform data conversion, cleaning, selection, etc. by himself; secondly, even if the website provides the query function, the user needs to set conditions to obtain the desired result because of numerous conditions for data query, and most websites can only provide query according to certain indexes and cannot comprehensively meet the query requirement; third, the website technology is a technology that requires a user to actively interact with the user, that is, if the user does not browse the website, the website cannot serve the user, in the modern society, the work and life rhythm of people is continuously accelerated, and many professionals cannot extract a large amount of time to visit the website, so that a large amount of information cannot be obtained, or even if the information is obtained, the real-time performance of the information is low. The method is not beneficial to professionals in the industry of labor-breaking, and a large amount of information needed by the professionals can be acquired timely and purposefully.

Second, mobile display technology (including APP, WeChat public account, WeChat applet, etc.)

The mobile display technology refers to a mobile webpage or a native user interface program realized by technologies such as Html, Html5, CSS, Javascript, Java, PHP, NET, Swift and the like, a C/S architecture is adopted, a server is deployed by a server, a user side can be installed on user mobile equipment or embedded into platforms such as WeChat and the like, the user side can access the server through an IP address and a domain name, and through the mode, the user can be allowed to access and browse query information. Such techniques may provide comprehensive browsing and querying of information. But the problem is that it does not cross platforms and must fit the corresponding operating system or rely on the platform. By means of the technology, the efficiency of the users in finding and acquiring the information needed by the users is low. This is because, first, the user must browse information extensively, select the information that the user wants from it, and then copy and record, and if the format is not the format that the user wants finally, then the user must also perform data conversion, cleaning, selection, etc. by himself; secondly, even if the program provides the query function, the user needs to set conditions to obtain the desired result because of numerous conditions for data query, and most programs can only provide query according to certain indexes and cannot comprehensively meet the query requirement; third, although the mobile terminal can receive the push, the pushed data volume is limited, and the mobile device space is small, which is not suitable for browsing and operating a large amount of data. The method is not beneficial to professionals in the industry of labor-breaking, and a large amount of information needed by the professionals can be acquired timely and purposefully.

[ summary of the invention ]

The bankruptcy information service method based on big data collection, processing and display pushing is provided. Through big data collection, browsable bankruptcy case related data, bankruptcy debtor related data, bankruptcy professional articles and bankruptcy related public opinion data which are disclosed in the whole network range are collected. And acquiring preference data of the user on bankruptcy information through the user order. Through cloud computing and big data technology, data are extracted, converted and cleaned, scattered data are associated, and data concerned by or customized by a user are generated based on user preference data. And then the user interface layer is used for screening, classifying and typesetting. Data display and push are carried out through desktop application programs, webpage query, APP, WeChat public numbers, WeChat small programs, mails, short messages and the like. The method is divided into a popularization mode and a profit mode, and a data service engine comprises the following two parts:

promotion mode, order management and profit mode of service

The method takes the display and the pushing of the bankruptcy information data of the enterprise as a service method. The method comprises the steps of issuing organized, summarized and summarized articles, data and information related to bankruptcy of enterprises through various promotion modes including website webpages, WeChat public numbers, WeChat applets, mobile APPs, mail promotion, short message promotion and the like, and enabling users to know the existence of the service through accessing and browsing the articles, data, messages and the like. The user can make an order in the form of an offline order, a website order, a wechat public number, a wechat applet, a mobile APP, a mail, a telephone, a short message and the like. When placing an order, the user needs to provide a receiving channel for information pushing or displaying, and user preference data (such as concerned region, debtor industry, debtor name and the like). User preference data may also be obtained when a user browses the promotional schema of the service. The system generates service data by the data service engine according to the preference of each user (the generation mode is described below), and then pushes or displays the service data to the receiving channel appointed by the user. The overview of the design structure and the data flow of the method are shown in the attached figure 1.

The method takes data service fee and advertisement fee as main profit modes. The data service fee charges different fees according to the number of times of pushing or showing, coverage service life, data amount, version and the like. The advertisement fee refers to the fee charged by the third party for requiring the service to implant advertisements in the promotion modes of the service (including website pages, WeChat public numbers, WeChat applets, mobile APP, mail promotion, short message promotion and the like). The advertisement fee charges different fees according to times, the time length of the coverage period, the advertisement amount, the conditions of third-party industries and companies, versions and the like.

Data service engine

The data service engine is divided into the following components:

1. information collection layer

The information collection layer is the basis for supporting the whole service method and mainly collects related enterprise bankruptcy data in the whole network range by means of a programmed big data collection technology. The collection range comprises court announcements, court decisions, administrator announcements, creditor meeting information, auction information, recruitment announcements, bankruptcy professional technical articles, bankruptcy cases, government-disclosed bankruptcy enterprise information (comprising industry and commerce, tax, administrative permissions, penalties and the like), bankruptcy public opinion information (comprising news, WeChat, micro blogs, forums, posts, various official networks, third-party websites and the like). The method does not collect non-public and confidential information. The information collection layer can be closely matched with the information extraction layer and the information storage layer to form a reliable database and a file library.

2. Information extraction layer

The information extraction refers to the process of judging and extracting data before the enterprise bankruptcy information is collected by the information collection layer, the information is collected and the data is stored in the database and then used by a user. The information extraction layer supports the auxiliary information collection layer to collect data in a targeted manner, supports reprocessing of the information to obtain key information when the information is collected, and supports additional processing of the data to support differentiated services for users according to user preference data after the information is stored.

3. Information storage layer

Information storage refers to the process of storing collected enterprise bankruptcy information into a database or file. The information storage layer is one of the core parts of the method. The data service is carried out on the user through a large amount of acquired local data and files.

User preference data is also stored in the information storage layer. The preference data of the user can be obtained by filling in a form by the user when the user places an order to purchase the service, and also can be obtained by the method for popularizing the mode through user behaviors. User preference data includes, but is not limited to, user interest areas, provinces, cities, debtors, courts, and the like. The user preference data plays a role in data display and pushing of the user so as to achieve the purpose of pushing different data to different users.

4. Information cleansing, translation, and association layers.

The information cleaning and conversion layer is a set processing layer for carrying out operations such as standardization, formatting, filling, judgment, form conversion, arrangement conversion, field change, screening, statistics and the like on enterprise bankruptcy information of the database. And the data preparation layer is used for displaying and pushing different data for different users according to the user preference data. For example, data having a manager name field may be converted to "manager determined" as the status field.

The information cleansing, translation, and association layer may also associate scattered information. The association refers to that scattered information is aggregated together according to a certain field or a plurality of fields, so that the browsing and the formation of a comprehensive information set are facilitated. Different information and behaviors like corporate debtors are scattered across different data sources. Through the association of the information, the effect that all information of the same debtor is associated with 1+1>2 can be formed. The washing conversion association layer supports differentiated services and high-quality and high-performance services for users.

5. Information presentation and push layer

And the information display and push layer is an interface, a report and a data file for serving the user according to the enterprise bankruptcy information processed in the step. Information exposure refers to the manner in which a user is allowed to browse and query through programs including, but not limited to, desktop programs, web pages, mobile APPs, wechat public numbers, wechat applets, and the like. The information push refers to sending various Office files, PDF files, pictures, text files, database files and the like serving as attachments through mails, and pushing different information to different users through short messages and multimedia messages, mobile APP push, public number push, WeChat applet push and the like. The information display and push layer also comprises partial subprograms which are matched with the information cleaning, conversion and conversion layer, different data reports or files can be generated according to user preference data, and the information concerned by the user can be marked by colors, fonts, bold and black, artistic effects and the like according to the user preference data by using a marking method, so that the user can quickly lock the required information. The information display and push layer also makes data preparation and support for articles, data and information related to bankruptcy of enterprises, which are partially sorted, summarized and summarized in the service promotion mode.

The data service engine structure and data flow of the method are shown in figure 2.

[ abstract of technical implementation procedures ]

The technical implementation steps of the method are mainly to implement a data service engine, which comprises information collection, information extraction, information storage, information cleaning conversion and association, information display and pushing, and the service promotion mode and the order and payment collection function are implemented. And (3) sequentially developing each function, and connecting each step through interfaces, subprograms or batch processing and the like to finally form a complete enterprise bankruptcy information service function system.

[ technical implementation idea ]

The method is realized by a data service engine, a service promotion mode and an order management part:

the implementation of a data service engine:

1. information collection layer

The information collection is divided into two modes, namely system manual collection and system automatic collection. The manual collection is mainly to search network information manually, and after a target is found, the network information is input into a database through an interface.

The automatic collection is realized by utilizing program codes to automatically collect network public data. Automated collection can collect both structured and unstructured data. The structured data mainly refers to data which can be stored in a relational database, exists in the form of bars and fields, and is organized in the form of tables, such as debtor names, judgment court names, regions and the like. Unstructured data is data that cannot be organized in a structured form, such as pictures, audio and video, and other similar data.

The automatic collection program is mainly based on languages including but not limited to Python, Java, NET, etc., and cooperates with related software packages to automatically capture data on the network by writing a collector program or adopting the existing collector software and framework on the market. The specific flow is that a request is sent to a target data source by a fixed operation flow, after a response is obtained, a response structure is analyzed, and required data is obtained from the structure. The collector supports automatic generation of requests and url requests, timed starting and ending of tasks, multi-node task allocation and scheduling, docking with a database or a file system, and storing in the database or storing as a file at one time, at regular time or in real time.

To improve the production efficiency of the automated collection program, the collector supports a distributed job scheduling model. The collector ensemble may consist of a task scheduler and a task executor. The dispatcher can generate requests and request urls, distribute the requests and the request urls to different nodes, and uniformly manage and store collected data of different nodes into a database or store the collected data as files. The scheduler supports task deduplication and data deduplication, reducing resource consumption and improving efficiency. The task executor may execute a fixed collection flow according to the tasks allocated by the scheduler, and directly store the collected data in a storage or submit the collected data to the scheduler for unified storage. The executor generally has a plurality of (including one), can be composed of different servers and virtual servers, and can have different IP addresses. And only one task scheduler is generally responsible for uniformly commanding the actuators and coordinating data storage.

2. Information extraction layer

This layer may provide support for the entire method in the form of subroutines or interfaces.

Before the data is collected, the data judger can be embedded into the collector, and irrelevant data is skipped over, so that resources are not occupied. And whether the data is collected or not can be determined by evaluating the information relevancy, positive and negative surfaces, keywords, abstract and the like of the data source by utilizing a natural language processing technology.

When the information is acquired, the key information can be extracted by utilizing subprograms such as format matching, text statement matching and the like. A plain text announcement as published by a certain court is unstructured. The subprogram can analyze the section of pure words, extract and organize information such as an applicant, an application date, a judgment court, a loss time and the like into structured data by utilizing technologies such as format matching, text statement matching, natural language processing and the like, and can mark different data differently, for example, whether a bankruptcy manager sends a notice or a court sends a notice can be marked, which is beneficial to storing the notice into a database.

After the information is collected, before the information is used by a user, the key information can be extracted by utilizing subprograms such as format matching, text statement matching, natural language processing and the like according to the customization of the user. The additional key information is extracted and organized into structured data, which is beneficial to generating value-added services for customers.

3. Information storage layer

The local database can include but is not limited to structured databases such as MySQL, Oracle, DB2, SQL Server, etc., or unstructured databases such as MongoDB, Redis, etc., or big data storage ecological platform solutions such as Hadoop, etc. Or the data is stored as a file and directly stored in a memory or a storage medium.

The information storage layer may be a subroutine written in a language including, but not limited to, Python, Java,. NET, or an interface that interfaces with the information collection layer. The storage tiers may be centralized or distributed. Structured databases including but not limited to MySQL, Oracle, DB2, SQL Server, etc., or unstructured databases such as MongoDB, Redis, etc., or big data storage ecoplatforms such as Hadoop, etc., may be utilized, one or a combination of several of them. The storage mode of the storage layer is not always permanent disk storage, but can also be a cache database in the form of an in-memory database, which is beneficial to providing services for users quickly and with high quality.

User preference data is also stored in the information storage layer. The preference data of the user can be obtained by filling in a form by the user when the user places an order to purchase the service, and also can be obtained by the method for popularizing the mode through user behaviors. User preference data includes, but is not limited to, user interest areas, provinces, cities, debtors, courts, and the like. The user preference data plays a role in data presentation and pushing for the user.

4. Information cleansing, translation, and association layers.

The technologies used by the information washing, converting and associating layer can be structured databases including but not limited to MySQL, Oracle, DB2, SQL Server, etc., or unstructured databases such as MongoDB, Redis, etc., or large data storage processing ecological platforms such as Hadoop, Hive, Spark, etc., one or several of which are combined to provide data washing and converting functions. Or batch or one-time processing of data using batch programs or triggers written in languages including but not limited to Python, Java,. NET, etc.

5. Information presentation and push layer

The available website technologies for information presentation include, but are not limited to, website webpage programs implemented by technologies such as Html, Html5, CSS, Javascript, Java, PHP, and. NET, and technologies that employ a B/S architecture, a server is deployed by a private server or a cloud server, is accessible by an IP address and a domain name, and can allow a user to access and browse query information. Or a mobile web page or a native user interface program realized by technologies such as Html, Html5, CSS, Javascript, Java, PHP, NET, Swift and the like by using a mobile technology, a C/S architecture is adopted, a server is deployed by a server, a user side can be installed on user mobile equipment or embedded into platforms such as WeChat and the like, and the user side can access the server through an IP address and a domain name.

The information push technology can use a mobile webpage or a native user interface program (specific forms include mobile APP, wechat public number, wechat applet and the like) which can be opened by a user side and is realized by technologies such as Html, Html5, CSS, Javascript, Java, PHP, NET, Swift and the like, a C/S architecture is adopted, a server side is deployed by a server, the user side can be installed on user mobile equipment or embedded into a platform such as wechat and the like, and the user side interacts with the server side through an IP address and a domain name, so that the server side can be allowed to carry out data push. Or sending various Office files, PDF files, pictures, text files, database files and the like as attachments by mails by using technologies including but not limited to C, C + +, Java, NET, Office VBA and the like, or carrying information by using short message and multimedia message service.

The information display and push layer can support the embedding and displaying of the advertisement in the reserved positions of the website webpage, the mobile APP, the WeChat public account, the WeChat applet, the file and the like.

The information presentation and push layer can be deployed in a centralized way or in a distributed way. The significance of distributed deployment is that when the number of users is large, the users can be provided with services by a plurality of servers, so that the pressure on a single server is reduced, and the users can be provided with services quickly and safely.

Second, service promotion mode and order management

In order to obtain and implement data services for users. A service promotion mode needs to be established, and the form comprises a webpage, a WeChat public number, a WeChat applet, a mobile APP, a mail, a short message and the like. The popularization mode can reserve positions and support the embedding and displaying of advertisements. The promotion mode needs to be realized by using technologies including but not limited to Html, Html5, CSS, Javascript, Java, PHP,. NET, Swift and the like or a third-party template framework and the like, and a user ordering interface is established. The ordering interface requires the user to fill in data push and display channels, preference data (such as region, debtor industry, debtor name, etc.). After the user places an order, the system can obtain the user information and the preference data and complete money collection. The preference data of the user can also be analyzed and acquired in browsing and popularization modes of the user, including website webpages, WeChat public numbers, WeChat applets, mobile APP, mail popularization, short message popularization and the like, and browsing and other behaviors of the user are captured by the system during information.

[ PROBLEMS ] the present invention

The invention achieves the following beneficial effects through a series of functional design and development:

firstly, the information acquisition cost is greatly reduced: the bankruptcy information of the enterprise is gathered and associated through the method, the operations of browsing, summarizing, associating, downloading and formatting and the like on a scattered data source by a user are not needed, and the time consumption in the processes is also not needed. This greatly reduces labor costs and provides support for users without missing good business opportunities. Through the forms of pushing, preference identification and the like, the situation that a user actively interacts with passive interaction interfaces such as websites and the like is avoided, the user can obtain the latest information concerned by the user at the first time, the interference and the fatigue caused by a large amount of irrelevant information are not needed, and the time delay of knowing important information is also avoided. The data file sent by the method can support browsing of a desktop and a mobile terminal, and the short place that a data carrier cannot bear a large amount of data is avoided.

Secondly, the information can be accurately classified according to various parameters: the information is processed by the extraction layer, and diversified and accurate classification can be performed, such as classification according to the commercial value of the information and the business development requirements of interest relatives. It may also be classified by region, city, scale, etc. This helps bankruptcy case relatives to quickly find the information they need without being disturbed and encumbered by irrelevant, non-commercially valuable information.

Thirdly, the information integration service capability is strong: the integration of the information not only can facilitate a user to acquire the information of a plurality of information sources at one time, but also can exert the function of each piece of information to the maximum extent, and the effect of 1+1>2 is obtained. Firstly, the integration of the information can enable the information to obtain statistical value, statistics is carried out from the regional dimension and the time dimension of the information, and the functions of analyzing regional differences and predicting the trend of bankruptcy business can be achieved. Second, the integration of all relevant information related to the same debtor may maximize the value of the information. Information relating to the same debtor may appear at different information sources and at different points in time, and integrating such information may enable a user to understand case progress and timeline information from various perspectives. For example, the amount of the related information of one case can reflect the attention and the scale of the case; the information release timeline distribution can reflect the success of case progress to a certain extent. Even if the information value improvement brought by information integration is not considered, the information collection and arrangement can be realized for the user comprehensively, and the work of collecting and arranging the information by the user is reduced.

[ description of the drawings ]

FIG. 1 is a design structure overview and data flow diagram of the present method.

Fig. 2 is a schematic diagram of the data service engine structure and data flow of the present method.

[ detailed description ] embodiments

The specific implementation mode of the method can be carried out according to the technical realization thought basically, and the infrastructure and the safety strategy are planned comprehensively.

Hardware environment

The hardware environment can use a private server or a cloud server, so that smooth network is ensured, and the fixed IP address is possessed. A cluster of servers may be used for service or a single server may be used.

Software environment

The software environment uses an operating system including, but not limited to, Windows or linux. And installing a development language environment to support the work of each layer.

Third, information collection layer

The information collection layer needs to install a corresponding development language environment, for example, if the information collection layer is a Python development collector, Python language should be installed. Collectors are developed through programming languages that can collect both structured and unstructured data. Developing a task scheduler and a data storage layer docking interface.

If necessary, a distributed deployment method is adopted, the executor can be deployed on a plurality of (including one) physical servers or virtual servers, and a task scheduler is developed to be used as a command of the executor.

Second, information extraction layer

Subroutines or interfaces may be developed to assist in the operation of other layers. The data judger can be embedded into the collector to skip irrelevant data, so that the occupation of resources is avoided. The extractor can be developed to extract the key information using sub-programs such as format matching, text statement matching, natural language techniques, and the like. Or the data processor can be developed to extract the key information by utilizing subprograms of format matching, text statement matching, natural language processing and the like according to the customization of the user.

Third, information storage layer

The database program database required to be installed at the layer can include but is not limited to structured databases such as MySQL, Oracle, DB2 and SQL Server, or unstructured databases such as MongoDB and Redis, or large data storage ecological platform schemes such as Hadoop. Or the data is stored as a file and directly stored in a memory or a storage medium.

The information storage layer needs to be configured with parameters that allow subroutines or interfaces written in languages including, but not limited to, Python, Java,. NET, etc. to interface with the information collection layer. The storage tier may be centralized or distributed, and the distribution may ensure reliability of the service and provide better performance. The storage mode of the storage layer is not always permanent disk storage, but can also be a cache database in the form of an in-memory database, which is beneficial to providing services for users quickly and with high quality.

And fourthly, information cleaning, conversion and correlation layers.

The information cleaning, conversion and association layer can write script operations including but not limited to structured databases such as MySQL, Oracle, DB2, SQL Server, etc., or unstructured databases such as MongoDB, Redis, etc., or large data storage processing ecological platforms such as Hadoop, Hive, Spark, etc., one or a combination of several of them. Or batch or one-time processing of data using batch programs or triggers written in languages including but not limited to Python, Java,. NET, etc.

Fifth, information display and push layer

This layer needs to install Web services including but not limited to Tomcat, IIS, Apache, Nginx, WSGI, etc. A mail server needs to be installed or a mail push service is provided with a mail service provider by using a mail client including but not limited to outlook. And opening the short message service and providing the short message pushing service.

The information display can be realized by adopting a website program which is realized by technologies including but not limited to Html, Html5, CSS, Javascript, Java, PHP, NET and the like, a B/S framework is adopted, and a server is deployed by a private server or a cloud server and can be accessed through an IP address and a domain name. Or a mobile webpage or a native user interface program realized by technologies of Html, Html5, CSS, Javascript, Java, PHP,. NET, Swift and the like, adopts a C/S architecture, a server is deployed by a private server or a cloud server, a user side can be installed on user mobile equipment or embedded into platforms such as WeChat and the like, and the user side can access the server through an IP address and a domain name to allow the user side to interact with the server.

The information pushing technology can be a mobile webpage or a native user interface program realized by technologies such as Html, Html5, CSS, Javascript, Java, PHP,. NET, Swift and the like, a C/S architecture is adopted, a server is deployed by a private server or a cloud server, a user side can be installed on user mobile equipment or embedded into a platform such as WeChat and the like, and the user side interacts with the server through an IP address and a domain name. Or sending various Office files, PDF files, pictures, text files, database files and the like as attachments through mails by using technologies including but not limited to C, C + +, Java, NET, Office VBA and the like in cooperation with a mail server, a mail service provider, a mail client and the like, or carrying information by using a short message and multimedia message service.

The information presentation and push layer can be deployed in a centralized way or in a distributed way. The significance of distributed deployment is that when the number of users is large, the users can be provided with services by a plurality of servers, so that the pressure on a single server is reduced, and the users can be provided with services quickly and safely. A management background can operate and maintain user data and service data.

Network security

Network security is primarily the security of data. And a high-strength password is adopted for the data storage layer, so that data leakage caused by password cracking is prevented. The IP address, subnet mask and port number of the visitor are strictly restricted by including but not limited to an Iptables firewall, cloud service security group configuration. For a system management account, VPN login or a high-strength password is adopted, the password is changed at regular time, and strict limitation is performed on an IP address, a subnet mask and a port number. Meanwhile, a timing backup strategy is adopted to perform remote backup on all programs and data. The information display and push layer adopts high-strength passwords, regularly changes the passwords, deploys HTTPS and purchases third-party services to prevent tampering.

Seventh, service promotion mode and order management

The layer needs to use technologies including but not limited to Html, Html5, CSS, Javascript, Java, PHP,. NET, Swift, etc., or third-party template frameworks, etc., to develop and implement popularization modes, including website webpages, wechat public numbers, wechat applets, mobile APPs, mail popularization, short message popularization, etc., and a user ordering interface. The ordering interface requires the user to fill in the necessary acceptance path and preference data. After the user places an order, the system can obtain the user information and the preference data and complete money collection. The popularization mode of the method comprises a website webpage, a WeChat public number, a WeChat small program, a mobile APP, a mail, a short message and the like, wherein a user behavior tracking program needs to be implanted, or the user browsing behavior is logarithmized, abstracted, structured and formed into label data. The user preference data is obtained through labeling, further database processing or analysis and processing of an algorithm program written by Java, NET, Python and other languages.

Claims (1)

1. The bankruptcy information service method relates to internet, big data and cloud computing, and is used for collecting, processing and individually displaying and pushing data;

according to the method, through big data collection, browsable bankruptcy case related data, bankruptcy debtor related data, bankruptcy professional articles and bankruptcy related public opinion data which are disclosed in the whole network range are collected, user preference data is obtained based on user orders or user behaviors, through cloud computing and big data technology, data is extracted, converted, cleaned and correlated, based on the user preference data, data which is concerned by or customized by a user is generated, then a user interface layer is used for screening, classifying and typesetting, and finally data display and pushing are carried out through a desktop application program, webpage query, APP, WeChat public numbers, WeChat small programs, mails, short messages and the like, so that comprehensive, rapid, high-quality, personalized and thousand-face bankruptcy information data service is completed;

the method mainly relates to the organic combination and data interaction of four major parts and aspects of a user, a data service engine, a promotion mode and order management and related information of the enterprise bankruptcy in the whole network, and is a comprehensive service method which takes the user as a service object, takes the promotion mode and order management as a user acquisition and user preference data acquisition mode, takes the data service engine consisting of an information collection layer, an information extraction layer, an information storage layer, an information cleaning conversion and association layer, an information display and a push layer as a service core and takes the bankruptcy information of the enterprise in the whole network as a data source;

the information collection layer of the method mainly relies on a programmed big data collection technology to collect the relevant data of bankruptcy in the whole network range, and can collect the structured and unstructured data, based on languages including but not limited to Python, Java, NET and the like, and matched with relevant software packages, through compiling a collector program or adopting the existing collector software and framework on the market, the method can automatically capture the bankruptcy information data of enterprises on the network, support automatic generation of requests and url requests, start and end of tasks at regular time, distribute and dispatch multi-node tasks, butt joint with a database or a file system, store the bankruptcy information data into the database at one time, at regular time or in real time or store the bankruptcy information as a file, support a distributed work dispatching mode, and uniformly coordinate data storage;

before enterprise bankruptcy information is collected, information is collected and data is stored in a database and before a user uses the information, an information extraction layer can judge and extract the data, specifically, before the data is collected, a data judger can be embedded into a collector to skip irrelevant data to avoid occupying resources, a natural language processing technology can be used to evaluate the information correlation degree, positive and negative surfaces, key words, abstract and the like of a data source to determine whether the data is collected, when the information is collected, subprograms such as format matching, text statement matching, natural language processing and the like can be used to extract key information, different data can be labeled differently, and before the information is collected and the user uses the information, subprograms such as format matching, text statement matching, natural language processing and the like can be used according to the customization of the user, extracting the key information, extracting the additional key information and organizing the additional key information into structured data, so that value-added services can be generated for customers;

the information storage layer of the method can store the collected enterprise bankruptcy information into a database or a file, the database can comprise but not limited to structured databases such as MySQL, Oracle, DB2 and SQL Server, or unstructured databases such as MongoDB and Redis, or big data storage ecological platform schemes such as Hadoop, one or a plurality of combinations thereof, or the data is stored as a file and is directly stored in a memory or a storage medium, this layer may be a subroutine or interface written in a language including but not limited to Python, Java,. NET etc. that interfaces with the information collection layer, the system can be centralized or distributed, can be stored in a permanent disk, and can also be a cache database in the form of a memory database, and the user personalized requirements and the tag data are also stored in an information storage layer and play a role in displaying and pushing the data of the user so as to achieve the purpose of pushing different data to different users;

the information cleaning, conversion and association layer of the method can carry out operations such as standardization, formatting, filling, judgment, form conversion, arrangement conversion, field change, screening and statistics on enterprise bankruptcy information in an information storage layer, can carry out data preparation on different data displayed and pushed by different users according to user personalized requirements and label data, and the technology of the layer can be structured databases such as MySQL, Oracle, DB2 and SQL Server, unstructured databases such as MongoDB and Redis, or big data storage processing ecological platforms such as Hadoop, Hive and Spark, wherein one or more of the databases are combined, and the layer has data cleaning and conversion functions, or can be batch processing programs or triggers written by languages such as Python, Java and NET, and can carry out batch processing or one-time processing on the data;

the information display and push layer of the method can serve users through interfaces, reports and data files, and is developed and realized through technologies including but not limited to Html, Html5, CSS, Javascript, Java, PHP,. NET, Swift and the like or third-party template frames and the like, the forms include but not limited to desktop programs, web pages, mobile APP, WeChat public numbers, WeChat small programs, mails, short messages and the like, the user is allowed to browse and inquire, or the data is received through various Office files, PDF files, pictures, text files, database files and the like without active interaction of the user, and different data reports or files are generated according to the personalized requirements of the user and the label data by matching with an information cleaning, conversion and association layer, or a labeling method can be utilized, according to the personalized requirements of the user and the label data, the information concerned by the user includes but not limited to colors, color, and the like, The marks of characters, bold and black, artistic effects and the like are marked, so that a user can quickly lock the required information and can reserve advertisement positions to realize a profit mode of the advertisement;

the method is characterized in that a popularization mode is developed and realized through technologies such as but not limited to Html, Html5, CSS, Javascript, Java, PHP,. NET, Swift and the like or a third-party template frame and the like, the modes include but not limited to website webpages, mobile APP, WeChat public numbers, WeChat applets, mails, short messages and the like, articles, data and information which are arranged, collected and summarized and related to enterprise bankruptcy are issued, a user is made to know the existence of the service through user access and browsing of the articles, data, messages and the like, meanwhile, browsing and behaviors of the user are also used as an obtaining mode of user preference data and are stored in an information storage layer after obtaining, and the popularization mode can reserve positions to support embedding and displaying of advertisements;

order management of the method is achieved through technologies such as but not limited to Html, Html5, CSS, Javascript, Java, PHP, NET and Swift or through development of a third-party template frame, the forms include but not limited to website webpages, mobile APP, WeChat public numbers, WeChat applets, mails, short messages and the like, users can place orders in the forms of offline ordering, webpage ordering, WeChat public numbers, WeChat applets, mobile APP, mails, telephones, short messages and the like, receiving channels for information pushing or displaying and user preference data (such as concerned, debtor industries, regional debtor names and the like) need to be provided when the users place orders, and therefore a data service engine can push or display the data to the receiving channels appointed by the users after generating the data according to the requirements of each user.

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