CN112465564A - Supplier recommendation method, device and terminal - Google Patents
Supplier recommendation method, device and terminal Download PDFInfo
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Abstract
The invention discloses a supplier recommendation method, a supplier recommendation device and a supplier recommendation terminal, wherein the supplier recommendation method comprises the following steps: collecting user information from a bidding system, the user information including vendor information for providing a product; carrying out data preprocessing on the supplier information; modeling the preprocessed supplier information according to different recommended dimensions; grading the recommended modeling result according to the rule requirement of the service; the highest scoring provider information is recommended. The method can enable an enterprise to quickly select the suppliers suitable for the enterprise requirements, and further reduces the cost loss of manpower, material resources and the like.
Description
Technical Field
The invention relates to the technical field of provider recommendation, in particular to a provider recommendation method, a provider recommendation device and a provider recommendation terminal.
Background
At present, the scale of an enterprise is continuously increased, the required products are increased, when the enterprise needs to buy the products, the enterprise mainly searches for a proper supplier in a mode of manually screening enterprise information, along with the huge number of suppliers in a library in a bidding system, each piece of supplier information data cannot be comprehensively inquired in manual inquiry, and errors easily occur in a manual judgment mode, so that the supplier meeting the actual requirements of the enterprise cannot be accurately selected. Therefore, how to select a supplier suitable for the enterprise is particularly important in combination with the actual demand of the enterprise for the product.
Disclosure of Invention
Aiming at the problems, the invention provides a method, a device and a terminal for intelligently recommending suppliers.
In order to solve the above technical problems, a first aspect of the present invention provides a technical solution: a supplier recommendation method comprising the steps of:
s1, collecting user information from a bidding system, wherein the user information comprises supplier information of a provided product;
s2, carrying out data preprocessing on the supplier information;
s3, modeling the preprocessed supplier information according to different recommended dimensions;
s4, scoring the recommended modeling result according to the rule requirement of the service;
and S5, recommending the provider information with the highest score.
Preferably, the supplier information in step S1 specifically includes: business licenses, business credit, financial indicators, certification, performance certification, and personnel information.
Preferably, the information of the suppliers is obtained from the bidding system, and the suppliers meeting the requirements of the enterprises are preliminarily screened according to the requirements of the enterprises.
Preferably, the data preprocessing in step S2 is to extract relevant feature parts from the information through data cleaning.
Preferably, the information is classified according to different characteristic attributes according to the supplier; historical bids, quotes and performance conditions of the suppliers are calculated.
The calculation method is specifically a collaborative filtering algorithm based on user recommendation, and the specific formula is as follows:
wherein
Is the basic information of the supplier,
the information of the product is provided to the supplier,
is the supplier's acceptance.
Preferably, step S3 specifically includes: and (3) carrying out weighting and mixing on the calculation results of the suppliers meeting the enterprise requirements through collaborative filtering to generate recommendations, adopting different recommendation technologies according to the actual conditions of different suppliers, combining and reordering the characteristics from different recommendation data sources, and carrying out modeling by using a plurality of dimensional characteristics to form a recommendation model.
Preferably, the recommendation model is output in a mapping mode, and the result is scored according to the rule requirements of the business.
The second aspect of the present invention provides a supplier recommendation apparatus, including:
an information acquisition module: the information acquisition module is used for acquiring user information from the bidding system, wherein the user information comprises supplier information for providing products;
a data preprocessing module: the data preprocessing module is used for preprocessing the data of the supplier information;
a recommendation modeling module: the recommendation modeling module is used for modeling the preprocessed supplier information according to different recommendation dimensions;
a scoring module: the scoring module is used for scoring the recommended modeling result according to the rule requirement of the service;
a recommendation module: the recommending module is used for recommending the supplier information with the highest score.
A third aspect of the present invention provides a terminal comprising a processor and a memory, the memory having a computer program stored therein, the processor being configured to execute the computer program to perform a method for implementing the above.
A storage medium according to a fourth aspect of the present invention stores a computer program executable to implement the above-described method when executed.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, supplier information is obtained from the bidding system, relevant characteristics are extracted through data cleaning, different characteristics are subjected to collaborative filtering calculation, and modeling analysis is carried out by utilizing characteristics of multiple dimensions, so that an enterprise can quickly select suppliers suitable for enterprise requirements, and further the cost loss of manpower, material resources and the like is reduced.
Drawings
Fig. 1 is a flowchart of a supplier recommendation method.
Fig. 2 is a schematic diagram of a supplier recommendation device.
Detailed Description
The following examples are further illustrative of the present invention and are not intended to be limiting thereof.
Referring to fig. 1, the present embodiment provides the following technical solutions: a supplier recommendation method comprising the steps of:
step S1, collecting user information from the bidding system, wherein the user information comprises supplier information for providing products;
in some embodiments of the present application, the supplier information in step S1 specifically includes: business licenses, business credit, financial indicators, certification, performance certification, and personnel information.
In some embodiments of the present application, the supplier information is obtained from the bidding system, and the suppliers meeting the enterprise requirements are preliminarily screened according to the enterprise requirements.
Step S2, data preprocessing is carried out on the supplier information;
in some embodiments of the present application, the data preprocessing in step S2 is to extract relevant feature parts from the information through data cleaning. The cleaned data can be directly sent to the recommendation model for analysis.
In some embodiments of the present application, the classification is based on vendor information according to different characteristic attributes; historical bids, quotes and performance conditions of the suppliers are calculated. The actual condition of the supplier is calculated in an all-around manner through the information of the supplier, so that the tender system can conveniently score the supplier.
The calculation method is specifically a collaborative filtering algorithm based on user recommendation, and the specific formula is as follows:
wherein
Is the basic information of the supplier,
the information of the product is provided to the supplier,
is the supplier's acceptance.
Step S3, modeling the preprocessed supplier information according to different recommended dimensions;
in some embodiments of the present application, step S3 specifically includes: and (3) carrying out weighting and mixing on the calculation results of the suppliers meeting the enterprise requirements through collaborative filtering to generate recommendations, adopting different recommendation technologies according to the actual conditions of different suppliers, combining and reordering the characteristics from different recommendation data sources, and carrying out modeling by using the characteristics of multiple dimensions to form a recommendation model.
Step S4, scoring the result of the recommendation modeling according to the rule requirement of the service;
in some embodiments of the present application, the output result of the recommendation model by mapping is scored according to the rule requirement of the business.
In step S5, the highest-scoring provider information is recommended.
According to the invention, supplier information is obtained from the bidding system, relevant characteristics are extracted through data cleaning, different characteristics are subjected to collaborative filtering calculation, and modeling analysis is carried out by utilizing characteristics of multiple dimensions, so that an enterprise can quickly select suppliers suitable for enterprise requirements, and further the cost loss of manpower, material resources and the like is reduced.
Referring to fig. 2, the present embodiment provides a supplier recommendation apparatus 20, including:
the information collecting module 201: the information acquisition module is used for acquiring user information from the bidding system, wherein the user information comprises supplier information for providing products;
the data preprocessing module 202: the data preprocessing module is used for preprocessing the data of the supplier information;
recommendation modeling module 203: the recommendation modeling module is used for modeling the preprocessed supplier information according to different recommendation dimensions;
the scoring module 204: the scoring module is used for scoring the recommended modeling result according to the rule requirement of the service;
the recommendation module 205: the recommending module is used for recommending the supplier information with the highest score.
The present embodiment provides a terminal, which includes a processor and a memory, where the memory stores a computer program, and the processor is configured to execute the computer program to perform the method for implementing the foregoing.
The present embodiment is a storage medium storing a computer program that can be executed, and when executed, implements the above-described method.
It is understood that in the preferred embodiment provided by the present invention, the terminal device may be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto.
The present invention provides a readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of a supplier recommendation method according to any of the first aspects.
Illustratively, a computer program can be partitioned into one or more modules, which are stored in memory and executed by a processor to implement the present invention. One or more of the modules may be a sequence of computer program instruction segments for describing the execution of a computer program in a computer device that is capable of performing certain functions.
Those skilled in the art will appreciate that the above description of a computer apparatus is by way of example only and is not intended to be limiting of computer apparatus, and that the apparatus may include more or less components than those described, or some of the components may be combined, or different components may be included, such as input output devices, network access devices, buses, etc.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like which is the control center for the computer device and which connects the various parts of the overall computer device using various interfaces and lines.
The memory may be used to store the computer programs and/or modules, and the processor may implement various functions of the computer device by running or executing the computer programs and/or modules stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The modules/units integrated by the computer device may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as separate products. Based on such understanding, all or part of the flow in the method according to the above embodiments may be implemented by a computer program, which may be stored in a computer readable storage medium and used by a processor to implement the steps of the above embodiments of the method. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, electrical signals, software distribution medium, and the like.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A supplier recommendation method, comprising the steps of:
s1, collecting user information from a bidding system, wherein the user information comprises supplier information of a provided product;
s2, carrying out data preprocessing on the supplier information;
s3, modeling the preprocessed supplier information according to different recommended dimensions;
s4, scoring the recommended modeling result according to the rule requirement of the service;
and S5, recommending the provider information with the highest score.
2. The supplier recommendation method according to claim 1, wherein the supplier information in step S1 specifically includes: business licenses, business credit, financial indicators, certification, performance certification, and personnel information.
3. The supplier recommendation method according to claim 1, wherein the step S1 specifically includes: and acquiring information of the suppliers from the bidding system, and primarily screening the suppliers meeting the enterprise requirements according to the requirements of the enterprises.
4. The supplier recommendation method according to claim 1, wherein the data preprocessing in step S2 is to extract relevant feature parts from the information by data cleaning.
5. The supplier recommendation method according to claim 4, wherein the suppliers are classified according to different characteristic attributes based on their information; calculating the historical bidding, quotation and performance conditions of the suppliers;
the calculation method is specifically a collaborative filtering algorithm based on user recommendation, and the specific formula is as follows:
wherein
Is the basic information of the supplier,
the information of the product is provided to the supplier,
is the supplier's acceptance.
6. The supplier recommendation method according to claim 1, wherein the step S3 specifically includes: and (3) carrying out weighting and mixing on the calculation results of the suppliers meeting the enterprise requirements through collaborative filtering to generate recommendations, adopting different recommendation technologies according to the actual conditions of different suppliers, combining and reordering the characteristics from different recommendation data sources, and carrying out modeling by utilizing multiple dimensions to form a recommendation model.
7. The supplier recommendation method according to claim 1, wherein the output result of the recommendation model by means of mapping is scored according to the rule requirements of the business.
8. An apparatus for vendor recommendation, comprising:
an information acquisition module: the information acquisition module is used for acquiring user information from the bidding system, wherein the user information comprises supplier information for providing products;
a data preprocessing module: the data preprocessing module is used for preprocessing the data of the supplier information;
a recommendation modeling module: the recommendation modeling module is used for modeling the preprocessed supplier information according to different recommendation dimensions;
a scoring module: the scoring module is used for scoring the recommended modeling result according to the rule requirement of the service;
a recommendation module: the recommending module is used for recommending the supplier information with the highest score.
9. A terminal, comprising a processor and a memory, the memory having stored thereon a computer program, the processor being configured to execute the computer program to perform the method of any of claims 1 to 7.
10. A storage medium storing a computer program executable to perform the method of any one of claims 1 to 7 when executed.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202011446774.9A CN112465564A (en) | 2020-12-11 | 2020-12-11 | Supplier recommendation method, device and terminal |
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| CN202011446774.9A CN112465564A (en) | 2020-12-11 | 2020-12-11 | Supplier recommendation method, device and terminal |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113837793A (en) * | 2021-08-25 | 2021-12-24 | 杭州杰牌传动科技有限公司 | Supplier recommendation method and device, storage medium and terminal |
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| CN105205188A (en) * | 2015-11-04 | 2015-12-30 | 用友网络科技股份有限公司 | Method and device for recommending purchase material suppliers |
| CN107392426A (en) * | 2017-06-20 | 2017-11-24 | 国网辽宁省电力有限公司 | The evaluation and system of selection of a kind of electricity provider |
| CN109086281A (en) * | 2017-06-14 | 2018-12-25 | 成都淞幸科技有限责任公司 | A kind of supplier's recommended method based on arest neighbors Collaborative Filtering Recommendation Algorithm |
| US20200126035A1 (en) * | 2017-04-26 | 2020-04-23 | Beijing Xiaodu Information Technology Co., Ltd. | Recommendation method and apparatus, electronic device, and computer storage medium |
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2020
- 2020-12-11 CN CN202011446774.9A patent/CN112465564A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105205188A (en) * | 2015-11-04 | 2015-12-30 | 用友网络科技股份有限公司 | Method and device for recommending purchase material suppliers |
| US20200126035A1 (en) * | 2017-04-26 | 2020-04-23 | Beijing Xiaodu Information Technology Co., Ltd. | Recommendation method and apparatus, electronic device, and computer storage medium |
| CN109086281A (en) * | 2017-06-14 | 2018-12-25 | 成都淞幸科技有限责任公司 | A kind of supplier's recommended method based on arest neighbors Collaborative Filtering Recommendation Algorithm |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113837793A (en) * | 2021-08-25 | 2021-12-24 | 杭州杰牌传动科技有限公司 | Supplier recommendation method and device, storage medium and terminal |
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Application publication date: 20210309 |