WO2019024496A1 - Procédé de recommandation d'entreprise et serveur d'application - Google Patents

Procédé de recommandation d'entreprise et serveur d'application Download PDF

Info

Publication number
WO2019024496A1
WO2019024496A1 PCT/CN2018/077656 CN2018077656W WO2019024496A1 WO 2019024496 A1 WO2019024496 A1 WO 2019024496A1 CN 2018077656 W CN2018077656 W CN 2018077656W WO 2019024496 A1 WO2019024496 A1 WO 2019024496A1
Authority
WO
WIPO (PCT)
Prior art keywords
enterprise
information
demand
target
target enterprise
Prior art date
Application number
PCT/CN2018/077656
Other languages
English (en)
Chinese (zh)
Inventor
汪伟
徐冰
王鸿滨
朱伟峰
肖京
Original Assignee
平安科技（深圳）有限公司
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by 平安科技（深圳）有限公司 filed Critical 平安科技（深圳）有限公司
Publication of WO2019024496A1 publication Critical patent/WO2019024496A1/fr

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
    • G06F16/90—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

Definitions

  • the present application relates to the field of communications technologies, and in particular, to an enterprise recommendation method and an application server.
  • the present application proposes an enterprise recommendation method and an application server, which can actively acquire the demand information of the enterprise, and recommend a matching enterprise for the enterprise according to the demand information of the enterprise.
  • the present application provides an application server including a memory, a processor, and an enterprise recommendation program stored on the memory and executable on the processor, the enterprise recommendation program
  • the following steps are implemented when executed by the processor:
  • the present application further provides an enterprise recommendation method, which is applied to an application server, and the method includes:
  • the present application further provides a computer readable storage medium storing an enterprise recommendation program, the enterprise recommendation program being executable by at least one processor to enable the At least one processor performs the steps of the enterprise recommendation method as described above.
  • the application server, the enterprise recommendation method, and the computer readable storage medium proposed by the present application first establish an enterprise feature table in advance; and then, according to the enterprise feature table, establish a matching table of supply and demand relationships of each enterprise; And obtaining the demand information of the target enterprise; finally, recommending the matching enterprise for the target enterprise according to the demand information and the enterprise supply and demand relationship matching table.
  • the disadvantages of the prior art enterprises spending a large amount of time and manpower actively searching for the cooperative enterprise, actively obtaining the demand information of the target enterprise, and recommending the matching enterprise for the target enterprise according to the demand information of the target enterprise. Achieving intelligent and efficient corporate recommendation services.
  • FIG. 1 is a schematic diagram of an optional application environment of each embodiment of the present application.
  • FIG. 2 is a schematic diagram of an optional hardware architecture of the application server of FIG. 1;
  • FIG. 3 is a schematic diagram of program modules of the first, second, third and fourth embodiments of the enterprise recommendation procedure of the present application;
  • FIG. 4 is a schematic diagram of an implementation process of a first embodiment of a method for recommending an enterprise according to the present application
  • FIG. 5 is a schematic diagram of an implementation process of a second embodiment of a method for recommending an enterprise according to the present application
  • FIG. 6 is a schematic flowchart of an implementation process of a third embodiment of a method for recommending an enterprise according to the present application
  • FIG. 7 is a schematic diagram of an implementation process of a fourth embodiment of a method for recommending an enterprise according to the present application.
  • Mobile terminal 1 application server 2 The internet 3 Memory 11 processor 12 Network Interface 13 Corporate recommendation procedure 200 First building module 201 Second building module 202 Acquisition module 203 Recommended module 204
  • first, second and the like in the present application are for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. .
  • features defining “first” and “second” may include at least one of the features, either explicitly or implicitly.
  • the technical solutions between the various embodiments may be combined with each other, but must be based on the realization of those skilled in the art, and when the combination of the technical solutions is contradictory or impossible to implement, it should be considered that the combination of the technical solutions does not exist. Nor is it within the scope of protection required by this application.
  • FIG. 1 it is a schematic diagram of an optional application environment of each embodiment of the present application.
  • the present application is applicable to an application environment including, but not limited to, a mobile terminal 1, an application server 2, and a network 3.
  • the mobile terminal 1 may be a mobile phone, a smart phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a navigation device, an in-vehicle device, etc.
  • Mobile devices such as, and fixed terminals such as digital TVs, desktop computers, notebooks, servers, and the like.
  • the application server 2 may be a computing device such as a rack server, a blade server, a tower server, or a rack server.
  • the application server 2 may be a stand-alone server or a server cluster composed of multiple servers.
  • the network 3 may be an intranet, an Internet, a Global System of Mobile communication (GSM), a Wideband Code Division Multiple Access (WCDMA), a 4G network, Wireless or wired networks such as 5G networks, Bluetooth, Wi-Fi, and
  • the application server 2 is respectively connected to one or more of the mobile terminals 1 (only one shown in the figure) through the network 3, and each of the mobile terminals 1 is installed and operated.
  • the application client corresponding to the application server 2 (hereinafter referred to as "mobile terminal client").
  • the mobile terminal client is configured to create a long connection between the mobile terminal client and the application server 2 in response to an operation of the mobile terminal user, so that the mobile terminal client can pass the long connection and the The application server 2 performs data transmission and interaction.
  • the application server 2 when the enterprise recommendation program 200 is installed and run in the application server 2, when the enterprise recommendation program 200 is running, the application server 2 pre-establishes an enterprise feature table, according to the enterprise feature table. A matching table of the enterprise supply and demand relationship is established. After the application server 2 obtains the demand information of the target enterprise, the matching enterprise is recommended to the target enterprise according to the demand information and the enterprise supply and demand relationship matching table, so that the application server 2 The company can actively obtain the demand information of the enterprise, and recommend matching companies to the enterprise according to the demand information of the enterprise. Achieving intelligent and efficient corporate recommendation services.
  • FIG. 2 it is a schematic diagram of an optional hardware architecture of the application server 2 in FIG.
  • the application server 2 may include, but is not limited to, the memory 11, the processor 12, and the network interface 13 being communicably connected to each other through a system bus. It is pointed out that FIG. 2 only shows the mobile terminal 1 with the components 11-13, but it should be understood that not all illustrated components are required to be implemented, and more or fewer components may be implemented instead.
  • the memory 11 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (eg, SD or DX memory, etc.), and a random access memory (RAM). , static random access memory (SRAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), magnetic memory, magnetic disk, optical disk, and the like.
  • the memory 11 may be an internal storage unit of the application server 2, such as a hard disk or memory of the application server 2.
  • the memory 11 may also be an external storage device of the application server 2, such as a plug-in hard disk equipped on the application server 2, a smart memory card (SMC), and a secure digital number. (Secure Digital, SD) card, flash card, etc.
  • the memory 11 can also include both the internal storage unit of the application server 2 and its external storage device.
  • the memory 11 is generally used to store an operating system installed on the application server 2 and various types of application software, such as program codes of the enterprise recommendation program 200. Further, the memory 11 can also be used to temporarily store various types of data that have been output or are to be output.
  • the processor 12 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments.
  • the processor 12 is typically used to control the overall operation of the application server 2, such as performing control and processing related to data interaction or communication with the mobile terminal 1.
  • the processor 12 is configured to run program code or process data stored in the memory 11, such as running the enterprise recommendation program 200 and the like.
  • the network interface 13 may comprise a wireless network interface or a wired network interface, which is typically used to establish a communication connection between the application server 2 and other electronic devices.
  • the network interface 13 is mainly used to connect the application server 2 to one or more mobile terminals 1 through the network 3, and the application server 2 and the one or more mobiles. A data transmission channel and a communication connection are established between the terminals 1.
  • the present application proposes an enterprise recommendation program 200.
  • the enterprise recommendation program 200 may be divided into one or more modules, and the one or more modules are stored in the memory 11 and are composed of one or more processors (this embodiment) This is performed by the processor 12) to complete the application.
  • the industry recommendation program 200 can be divided into a first establishing module 201, a second establishing module 202, an obtaining module 203, and a recommending module 204.
  • the program module referred to in the present application refers to a series of computer program instruction segments capable of performing a specific function, and is more suitable than the program to describe the execution process of the industry recommendation program 200 in the application server 2. The functions of each of the program modules 201-204 will be described in detail below.
  • the first establishing module 201 is configured to pre-establish an enterprise feature table in a database of the application server 2.
  • the manner of establishing the enterprise feature table in advance may be that the administrator imports through the database in the background of the application server 2.
  • the manner of establishing the enterprise feature table in advance may also be that the first establishing module 201 of the application server 2 establishes an enterprise feature table by using news information.
  • the enterprise information information includes: a title of the information, an industry type, and an information content.
  • the second establishing module 202 is configured to establish, according to the enterprise feature table, each enterprise supply and demand relationship matching table.
  • the enterprise supply and demand relationship matching table is established according to the information information of the enterprise feature table.
  • the enterprise in order to perform enterprise information matching more quickly, the enterprise may be classified according to the enterprise information, that is, the supply and demand relationship matching table further includes the category of the enterprise.
  • the category of the enterprise For example: clothing industry, financial industry, manufacturing and so on.
  • Each business category is not limited to only one category depending on the business situation.
  • company A can belong to both the financial industry and the electronics industry.
  • the enterprise supply and demand relationship matching table can be in the following form:
  • Company Name Business category supply demand > A Electronics Industry / Financial Industry Fund management IC component B Financial sector Provide loans C it Electronic component supplier D it Electronic component manufacturing
  • the obtaining module 203 is configured to acquire demand information of the target enterprise. Specifically, the obtaining module 203 can obtain the demand information of the target enterprise through the mobile terminal 1. For example, the information about the target enterprise can be obtained through the operation of the client user of the mobile terminal 1 and the information of the client of the mobile terminal 1. The specific steps are as follows. Carry out the details.
  • the recommendation module 204 is configured to recommend a matching enterprise to the target enterprise according to the requirement information and the enterprise supply and demand relationship matching table.
  • the recommendation module 204 generates a recommendation list to the target enterprise.
  • the first establishing module 201 of the application server 2 pre-establishes an enterprise feature table
  • the second establishing module 202 establishes each enterprise supply and demand relationship matching table according to the enterprise feature table
  • the obtaining module 203 acquires a target enterprise.
  • Demand information The recommendation module 204 recommends a matching enterprise for the target enterprise according to the demand information and the enterprise supply and demand relationship matching table.
  • the application server 2 can actively acquire the demand information of the enterprise, and recommend the matching enterprise to the enterprise according to the demand information of the enterprise. Achieving intelligent and efficient corporate recommendation services.
  • the enterprise recommendation program 200 proposed by the present application firstly establishes an enterprise feature table in advance, and secondly, establishes each enterprise supply and demand relationship matching table according to the enterprise feature table, and then, the application server 2
  • the mobile terminal 1 can obtain the demand information of the target enterprise, and finally, the matching enterprise is recommended for the target enterprise according to the demand information and the enterprise supply and demand relationship matching table.
  • the disadvantages of the prior art enterprises spending a lot of time and manpower to actively search for the cooperative enterprise are avoided, the enterprise demand information is actively obtained, and the matching enterprise is recommended for the enterprise according to the demand information of the enterprise. Achieving intelligent and efficient corporate recommendation services.
  • the first establishing module 201 is further configured to:
  • Extracting the keyword of the enterprise calculating the weight value of each keyword; sorting the weight value; selecting the sorted weight value according to the preset range, and using the keyword corresponding to the selected weight value as the enterprise label.
  • the extracted enterprise keywords are composed of an enterprise industry, a supply and demand type, a city, a common time, and an information category.
  • the extracted enterprise keywords can be obtained through the portal, news media, corporate information activities, etc. of the enterprise of the mobile terminal 1.
  • enterprise introduction, enterprise supply and demand resource description, information article information, activity content description information, and news information can all be used as sources of information for extracting corporate keywords.
  • the first establishing module 201 assigns different weights to each keyword, and calculates a weight value of each keyword, and at the same time, sorts the weight values and selects the sorted weight values according to the preset range (for example, Select the keyword with the highest weight value, such as the top three keywords. Finally, the keyword corresponding to the selected weight value is used as the enterprise label.
  • the information of the A company is obtained through the information information of the mobile terminal 1, "electronic supplier”, “requires financing of 10 million US dollars”, “investment new factory”, “IC chip supply”, “employee 10000+”, " The top 500 technology, "the number of patent applications is over one hundred”, etc., the weight for the industry category is 4 points, the weight value of the supply and demand relationship is 3 points, and the others are 2 points.
  • the keyword rankings of A companies are: first place: “electronic supplier” 4 points; second place: “requires financing 10 million US dollars” 3 points; second place: “IC chip supply” 3 points; fourth Name: “Investment in new factory”, “Employees 10000+”, “Technology Top 500”, “Other patents and other keywords”.
  • the first establishing module 201 of the application server 2 can set the top three keywords of the score to be the keywords of the A enterprise, so the keywords of the A enterprise are “electronic suppliers”, “need to raise 10 million US dollars” and “IC chip supply”. ". It should be noted that the extracted keywords are not limited to the top three keywords in the weight ranking, and can be set according to user needs.
  • the obtaining module 203 is further configured to:
  • the operation behavior of the user of the target enterprise on the client of the mobile terminal 1 is as follows:
  • each operation behavior will have a frequency record, and the information content involved in each operation behavior will correspond.
  • the corresponding label description According to these operational behaviors and label descriptions, the demand information of the enterprise where the user is located can be extracted.
  • the obtaining module 203 is further configured to perform semantic analysis according to the information information to obtain a requirement change of the target enterprise. Further, the obtaining module 203 further changes the enterprise feature table and the enterprise supply and demand relationship matching table according to the information of the demand change.
  • the application server 2 judges the change of the business direction and the development plan through the semantic analysis of the news sentences, and then provides the high-quality suppliers and suppliers in the industry.
  • the obtaining module 203 records the operation behavior of the user of the target enterprise; records the frequency of the operation behavior and the label description corresponding to the information content involved in the operation behavior; and according to the operation behavior and the The tag description extracts the demand information of the target enterprise.
  • the obtaining module 203 further performs semantic analysis according to the information information, and acquires a requirement change of the target enterprise.
  • the enterprise recommendation program 200 proposed by the present application can timely know the change of the target enterprise according to the operation behavior of the user of the target enterprise and the semantic analysis of the information information, and then recommend a high-quality matching enterprise to the target enterprise. .
  • the recommendation module 204 is further configured to:
  • the recommendation module 204 assigns different weight values to the industry, keywords, demand/supply, etc. of the enterprise.
  • the target enterprises that can limit the demand can only be selected from the enterprises that have the supply business, regardless of the enterprises with only the demand.
  • the B enterprise provides a loan
  • the C enterprise is an electronic component supplier
  • the D enterprise is an electronic component manufacturing
  • the preset parameters are set to “professionality” and “supply”, and the “professional” and “supply” weights are 0.6 and 0.4 respectively, and the “professional degree” is 3 points, and the manufacturing is 5 Points, the other is 1 point; the supplier in the "supply” is 2 points, the manufacturer is 3 points, and the others are 1 point.
  • the enterprise recommendation program 200 proposed by the present application can also calculate the matching degree of each enterprise relative to the target enterprise according to the entries of the enterprise supply and demand relationship matching table, and sort according to the matching degree. Generate a list of recommendations for the target enterprise.
  • the present application also proposes a company recommendation method.
  • FIG. 4 it is a schematic diagram of an implementation process of the first embodiment of the enterprise recommendation method of the present application.
  • the order of execution of the steps in the flowchart shown in FIG. 4 may be changed according to different requirements, and some steps may be omitted.
  • step S401 an enterprise feature table is pre-established in the database of the application server 2.
  • the manner of establishing the enterprise feature table in advance may be that the administrator imports through the database in the background of the application server 2.
  • the manner of establishing the enterprise feature table in advance may also be that the application server 2 establishes an enterprise feature table through the news information.
  • the enterprise information information includes: a title of the information, an industry type, and an information content. The specific steps will be described in detail in the second embodiment (see FIG. 5) of the company recommendation method of the present application.
  • Step S402 establishing, according to the enterprise feature table, a matching table of supply and demand relationships of each enterprise.
  • the application server 2 establishes a supply and demand relationship matching table of the enterprise according to the information information of the enterprise feature table.
  • the enterprise in order to perform enterprise information matching more quickly, the enterprise may be classified according to the enterprise information, that is, the supply and demand relationship matching table further includes the category of the enterprise.
  • the category of the enterprise For example: clothing industry, financial industry, manufacturing and so on.
  • Each business category is not limited to only one category depending on the business situation.
  • company A can belong to both the financial industry and the electronics industry.
  • the enterprise supply and demand relationship matching table can be in the following form:
  • Company Name Business category supply demand > A Electronics Industry / Financial Industry Fund management IC component B Financial sector Provide loans C it Electronic component supplier D it Electronic component manufacturing
  • Step S403 obtaining demand information of the target enterprise.
  • the application server 2 can obtain the demand information of the target enterprise through the mobile terminal 1.
  • the operation information of the client terminal of the mobile terminal 1 and the information information of the client of the mobile terminal 1 can be used to obtain the demand information of the target enterprise.
  • the third embodiment (see FIG. 6) of the company recommendation method of the present application will be described in detail.
  • Step S404 recommend matching companies for the target enterprise according to the demand information and the enterprise supply and demand relationship matching table. Specifically, the application server 2 generates a recommendation list to the target enterprise.
  • the application server 2 pre-establishes an enterprise feature table, and establishes a matching table of supply and demand relationships of the enterprises according to the enterprise feature table, and acquires the demand information of the target enterprise through the mobile terminal 1.
  • the application server 2 recommends a matching enterprise for the target enterprise according to the demand information and the enterprise supply and demand relationship matching table. In this way, the application server 2 can actively acquire the demand information of the enterprise, and recommend the matching enterprise to the enterprise according to the demand information of the enterprise. Achieving intelligent and efficient corporate recommendation services.
  • the enterprise recommendation method proposed by the present application firstly establishes an enterprise feature table in advance, and secondly, establishes each enterprise supply and demand relationship matching table according to the enterprise feature table, and then the application server 2 can
  • the mobile terminal 1 acquires the demand information of the target enterprise, and finally, the matching enterprise is recommended for the target enterprise according to the demand information and the enterprise supply and demand relationship matching table.
  • the disadvantages of the prior art enterprises spending a lot of time and manpower to actively search for the cooperative enterprise are avoided, the enterprise demand information is actively obtained, and the matching enterprise is recommended for the enterprise according to the demand information of the enterprise. Achieving intelligent and efficient corporate recommendation services.
  • the step of pre-establishing the enterprise feature table specifically includes:
  • Step S501 extracting a business keyword.
  • Step S502 calculating a weight value of each keyword.
  • Step S503 sorting the weight values.
  • Step S504 selecting the sorted weight values according to the preset range.
  • step S505 the keyword corresponding to the selected weight value is used as the enterprise label.
  • the extracted enterprise keywords are composed of an enterprise industry, a supply and demand type, a city, a common time, and an information category.
  • the extracted enterprise keywords can be obtained through the portal, news media, corporate information activities, etc. of the enterprise of the mobile terminal 1.
  • enterprise introduction, enterprise supply and demand resource description, information article information, activity content description information, and news information can all be used as sources of information for extracting corporate keywords.
  • the application server 2 assigns different weights to each keyword, and calculates the weight value of each keyword. At the same time, the weight values are sorted, and the sorted weight values are selected according to the preset range (for example, Select the keyword with the highest weight value, such as the top three keywords. Finally, the keyword corresponding to the selected weight value is used as the enterprise label.
  • the information of the A company is obtained through the information information of the mobile terminal 1, "electronic supplier”, “requires financing of 10 million US dollars”, “investment new factory”, “IC chip supply”, “employee 10000+”, " The top 500 technology, "the number of patent applications is over one hundred”, etc., the weight for the industry category is 4 points, the weight value of the supply and demand relationship is 3 points, and the others are 2 points.
  • the keyword rankings of A companies are: first place: “electronic supplier” 4 points; second place: “requires financing 10 million US dollars” 3 points; second place: “IC chip supply” 3 points; fourth Name: “Investment in new factory”, “Employees 10000+”, “Technology Top 500”, “Other patents and other keywords”.
  • the first establishing module 201 of the application server 2 can set the top three keywords of the score to be the keywords of the A enterprise, so the keywords of the A enterprise are “electronic suppliers”, “need to raise 10 million US dollars” and “IC chip supply”. ". It should be noted that the extracted keywords are not limited to the top three keywords in the weight ranking, and can be set according to user needs.
  • the enterprise recommendation method proposed by the present application can acquire enterprise characteristic information by acquiring tags of each enterprise according to the information information.
  • the step of acquiring the requirement information of the target enterprise includes:
  • Step S601 recording an operation behavior of a user of the target enterprise.
  • Step S602 recording the frequency of the operation behavior and the label description corresponding to the information content involved in the operation behavior.
  • Step S603 extracting demand information of the target enterprise according to the operation behavior and the label description.
  • the operation behavior of the user of the target enterprise on the client of the mobile terminal 1 is as follows:
  • each operation behavior will have a frequency record, and the information content involved in each operation behavior will correspond.
  • the corresponding label description According to these operational behaviors and label descriptions, the demand information of the enterprise where the user is located can be extracted.
  • the step of acquiring the requirement information of the target enterprise further includes:
  • step S604 semantic analysis is performed according to the information information, and the demand change of the target enterprise is obtained. Further, the application server 2 further changes the enterprise feature table and the enterprise supply and demand relationship matching table according to the information of the demand change.
  • the application server 2 judges the change of the business direction and the development plan through the semantic analysis of the news sentences, and then provides the high-quality suppliers and suppliers in the industry.
  • the application server 2 records the operation behavior of the user of the target enterprise; records the frequency of the operation behavior and the label description corresponding to the information content involved in the operation behavior; and according to the operation behavior and the The tag description extracts the demand information of the target enterprise.
  • the application server 2 also performs semantic analysis based on the information information to obtain a change in the requirements of the target enterprise.
  • the enterprise recommendation method proposed by the present application can timely know the target enterprise's demand change according to the user's operation behavior and the semantic analysis of the information information of the target enterprise, and then recommend a high-quality matching enterprise to the target. enterprise.
  • the step of recommending matching enterprises according to the requirement information and the enterprise supply and demand relationship matching table specifically includes:
  • Step S701 Select a plurality of preset parameters according to the entry of the enterprise supply and demand relationship matching table.
  • Step S702 assigning the plurality of preset parameters with different weights.
  • step S703 the matching degree of each enterprise with respect to the demand of the target enterprise is calculated.
  • Step S704 generating a recommendation list according to the calculated value of the matching degree.
  • the application server 2 gives the enterprise's industry, keywords, demand/supply, and the like different weight values.
  • the target enterprises that can limit the demand can only be selected from the enterprises that have the supply business, regardless of the enterprises with only the demand.
  • the B enterprise provides a loan
  • the C enterprise is an electronic component supplier
  • the D enterprise is an electronic component manufacturing
  • the preset parameters are set to “professionality” and “supply”, and the “professional” and “supply” weights are 0.6 and 0.4 respectively, and the “professional degree” is 3 points, and the manufacturing is 5 Points, the other is 1 point; the supplier in the "supply” is 2 points, the manufacturer is 3 points, and the others are 1 point.
  • the enterprise recommendation method proposed by the present application can also calculate the matching degree of each enterprise relative to the target enterprise according to the entry of the enterprise supply and demand relationship matching table, and according to the matching degree, The target company generates a list of recommendations.
  • the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is better.
  • Implementation Based on such understanding, the technical solution of the present application, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk,
  • the optical disc includes a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the methods described in the various embodiments of the present application.

Landscapes

  • Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

L'invention concerne un procédé de recommandation d'entreprise et un serveur d'application (2), le serveur d'application (2) comprenant une mémoire (11), un processeur (12) et un programme de recommandation d'entreprise (200) stocké dans la mémoire (11) et pouvant être exécuté sur le processeur (12); le programme de recommandation d'entreprise (200) exécute les étapes suivantes lors de l'exécution par le processeur (12) : l'établissement d'une table de caractéristiques d'entreprise à l'avance; l'établissement d'une table d'appariement de la relation offre-demande d'entreprise individuellement selon la table de caractéristiques d'entreprise; l'acquisition d'informations de demande d'une entreprise cible; et la recommandation d'une entreprise appariée à l'entreprise cible en fonction des informations de demande et de la table d'appariement de la relation offre-demande d'entreprise. Le serveur d'application (2) et le procédé de recommandation d'entreprise peuvent être utilisés pour acquérir activement des informations de demande d'une entreprise et recommander une entreprise correspondante à l'entreprise en fonction des informations de demande de l'entreprise.
PCT/CN2018/077656 2017-08-04 2018-02-28 Procédé de recommandation d'entreprise et serveur d'application WO2019024496A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201710658113.4 2017-08-04
CN201710658113.4A CN108427695A (zh) 2017-08-04 2017-08-04 企业推荐方法及应用服务器

Publications (1)

Publication Number Publication Date
WO2019024496A1 true WO2019024496A1 (fr) 2019-02-07

Family

ID=63155489

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2018/077656 WO2019024496A1 (fr) 2017-08-04 2018-02-28 Procédé de recommandation d'entreprise et serveur d'application

Country Status (2)

Country Link
CN (1) CN108427695A (fr)
WO (1) WO2019024496A1 (fr)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110377809A (zh) * 2019-06-19 2019-10-25 深圳壹账通智能科技有限公司 预设用户的资源获取资质生成方法及相关设备
CN112435051A (zh) * 2020-11-13 2021-03-02 北京创业光荣信息科技有限责任公司 一种关联企业的获取方法、电子设备、计算机可读存储介质及终端
CN112435052A (zh) * 2020-11-13 2021-03-02 北京创业光荣信息科技有限责任公司 一种关联企业的获取方法、电子设备、计算机可读存储介质及终端

Families Citing this family (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109359817A (zh) * 2018-09-13 2019-02-19 江苏站企动网络科技有限公司 一种企业信息分析管理系统
CN109300003B (zh) * 2018-09-17 2023-06-02 平安科技（深圳）有限公司 企业推荐方法、装置、计算机设备和存储介质
CN112528007B (zh) * 2019-09-19 2023-04-07 中冶赛迪信息技术(重庆)有限公司 一种招商项目的目标企业的确认方法及确认装置
CN110795471B (zh) * 2019-10-31 2022-06-07 北京金堤科技有限公司 数据匹配的方法及装置、计算机可读存储介质、电子设备
CN112231466A (zh) * 2020-10-21 2021-01-15 中国银行股份有限公司 撮合活动中的企业匹配方法及装置
CN112395501A (zh) * 2020-11-17 2021-02-23 航天信息股份有限公司 企业推荐方法、装置、存储介质及电子设备
CN113724032A (zh) * 2020-12-31 2021-11-30 京东城市(北京)数字科技有限公司 供需产品的匹配方法、装置、电子设备和存储介质
CN112800333B (zh) * 2021-02-04 2023-10-27 北京信息科技大学 企业用户服务的推荐方法、装置、设备及存储介质
CN113269516A (zh) * 2021-05-13 2021-08-17 企家有道网络技术(北京)有限公司 一种通过大数据提高企业能效的方法、装置及系统
CN114357308B (zh) * 2021-09-17 2022-09-02 北京能科瑞元数字技术有限公司 一种基于推荐的制造企业供需对接方法及装置
CN115080854A (zh) * 2022-06-29 2022-09-20 北京中关村软件园孵化服务有限公司 一种用于企业服务的数字化服务平台系统
CN116108275A (zh) * 2023-02-09 2023-05-12 深圳市鸿普森科技股份有限公司 一种服务需求匹配方法、系统、电子设备及存储介质

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103237018A (zh) * 2013-03-29 2013-08-07 东莞宇龙通信科技有限公司 一种客户端匹配方法、服务器及通信系统
CN106204094A (zh) * 2016-06-23 2016-12-07 东南大学 一种基于b2b平台的需求信息推送方法、装置
CN106383894A (zh) * 2016-09-23 2017-02-08 深圳市由心网络科技有限公司 一种企业供需信息匹配方法和装置
CN106934679A (zh) * 2015-12-29 2017-07-07 优信拍（北京）信息科技有限公司 信息匹配方法及装置

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150039549A1 (en) * 2013-07-30 2015-02-05 Reccosend LLC System and method for computerized recommendation delivery, tracking, and prioritization
CN106933969A (zh) * 2017-02-10 2017-07-07 九次方大数据信息集团有限公司 基于行业上下游关系的个性化推荐系统和推荐方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103237018A (zh) * 2013-03-29 2013-08-07 东莞宇龙通信科技有限公司 一种客户端匹配方法、服务器及通信系统
CN106934679A (zh) * 2015-12-29 2017-07-07 优信拍（北京）信息科技有限公司 信息匹配方法及装置
CN106204094A (zh) * 2016-06-23 2016-12-07 东南大学 一种基于b2b平台的需求信息推送方法、装置
CN106383894A (zh) * 2016-09-23 2017-02-08 深圳市由心网络科技有限公司 一种企业供需信息匹配方法和装置

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110377809A (zh) * 2019-06-19 2019-10-25 深圳壹账通智能科技有限公司 预设用户的资源获取资质生成方法及相关设备
WO2020253353A1 (fr) * 2019-06-19 2020-12-24 深圳壹账通智能科技有限公司 Procédé de génération de qualification d'acquisition de ressources pour un utilisateur prédéfini et dispositif associé
CN112435051A (zh) * 2020-11-13 2021-03-02 北京创业光荣信息科技有限责任公司 一种关联企业的获取方法、电子设备、计算机可读存储介质及终端
CN112435052A (zh) * 2020-11-13 2021-03-02 北京创业光荣信息科技有限责任公司 一种关联企业的获取方法、电子设备、计算机可读存储介质及终端
CN112435051B (zh) * 2020-11-13 2023-11-28 海创汇科技创业发展股份有限公司 一种关联企业的获取方法、电子设备、计算机可读存储介质及终端
CN112435052B (zh) * 2020-11-13 2023-11-28 海创汇科技创业发展股份有限公司 一种关联企业的获取方法、电子设备、计算机可读存储介质及终端

Also Published As

Publication number Publication date
CN108427695A (zh) 2018-08-21

Similar Documents

Publication Publication Date Title
WO2019024496A1 (fr) Procédé de recommandation d'entreprise et serveur d'application
US11263401B2 (en) Method and system for securely storing private data in a semantic analysis system
US8856229B2 (en) System and method for social networking
TWI677828B (zh) 基於資料源的業務客製裝置、方法及電腦可讀儲存介質
CN103620601B (zh) 在映射缩减过程中汇合表
CN111046237B (zh) 用户行为数据处理方法、装置、电子设备及可读介质
US9141656B1 (en) Searching using access controls
US11709878B2 (en) Enterprise knowledge graph
CN109614402B (zh) 多维数据查询方法和装置
WO2019085463A1 (fr) Procédé de recommandation de demande de service, serveur d'application et support de stockage lisible par ordinateur
US20150120708A1 (en) Information aggregation, classification and display method and system
WO2019095670A1 (fr) Procédé de suivi de performances de vente, serveur d'application et support de stockage lisible par ordinateur
US10536352B1 (en) Systems and methods for tuning cross-platform data collection
US20190294594A1 (en) Identity Data Enhancement
CN114240344A (zh) 企业人员数据处理方法、装置、计算机设备和存储介质
WO2019071964A1 (fr) Procédé d'élaboration de relation d'entreprise et serveur d'applications
CN107291923B (zh) 信息处理方法和装置
US20150363803A1 (en) Business introduction interface
US20140195462A1 (en) Data management system and tool
CN110674383B (zh) 舆情查询方法、装置及设备
US20210240928A1 (en) Mapping feedback to a process
WO2020024824A1 (fr) Procédé et dispositif de détermination d'un identifiant de statut d'utilisateur
US20140244741A1 (en) Computer-Implemented System And Method For Context-Based APP Searching And APP Use Insights
US20230297596A1 (en) Mutual Exclusion Data Class Analysis in Data Governance
CN115481026A (zh) 测试案例的生成方法、装置、计算机设备、存储介质

Legal Events

Date Code Title Description
NENP Non-entry into the national phase

Ref country code: DE

121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 18841321

Country of ref document: EP

Kind code of ref document: A1

122 Ep: pct application non-entry in european phase

Ref document number: 18841321

Country of ref document: EP

Kind code of ref document: A1