User-demand-oriented cloud manufacturing service recommendation method

A service recommendation, user-oriented technology, applied in the field of cloud manufacturing service recommendation, can solve the problems of semantic loss and low accuracy, and achieve the effects of strong pertinence, reliability assurance, and simple implementation.

Active Publication Date: 2015-06-24
BEIHANG UNIV
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

But the disadvantage is that the accuracy of the recommendation is not high, because t

Method used

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  • User-demand-oriented cloud manufacturing service recommendation method
  • User-demand-oriented cloud manufacturing service recommendation method
  • User-demand-oriented cloud manufacturing service recommendation method

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Embodiment Construction

[0033] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0034] The present invention is a cloud manufacturing service recommendation method oriented to user needs, such as figure 1 As shown, it mainly includes four parts: service classification specification and description specification establishment, construction of user demand text, processing user text and calculating similarity and obtaining appropriate recommended services.

[0035] (1) Establishment of service classification specifications and description specifications

[0036] The classification results are different under different service classification methods. For example, according to application areas, services may be divided into biology, mathematics, physics, etc., each of which corresponds to its own sub-category. If divided according to its existence, services may be divided into software, equipment, knowledge, and materials. Different users tend to...

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Abstract

The invention provides a user-demand-oriented cloud manufacturing service recommendation method. According to the method, firstly, part of information of classification and service description of cloud manufacturing is standardized; secondly, a certain number of users in some field and all services used by the users within a period of time are selected, and the names and brief introductions of the services are combined to texts for the users; the users with the similar demands are determined through the method of comparing the similarity of the texts; some users with the similarity approaching to some user are selected, and the service using situation of the user at some service type are compared; the services which are not used by the user but used by the similar users are recommended to the user. According to the method, the character similarity of all the users with the similar user demands on the demand for all types of services is taken into consideration, and the recommended services must be applied by other enterprises. The user-demand-oriented cloud manufacturing service recommendation method is very high in accuracy.

Description

Technical field [0001] The present invention designs a cloud manufacturing service recommendation method oriented to user needs. This method analyzes the services used by the user under the cloud manufacturing service classification system and service release standards, and uses the bag of words model to obtain similar needs as the target user Prone users. By comparing the differences between the two, select the appropriate service and recommend it to the target users. This method can regard the user's demand tendency as a connected whole, and the recommended services are more targeted, and all have been actually tested, and the reliability is guaranteed, which belongs to the manufacturing field. Background technique [0002] The recommendation system is a very important link in the current e-commerce, social, manufacturing and other platforms. The system can infer the direction that the user may be interested in based on some behaviors of the user, and recommend the content of...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q30/02
Inventor 张霖胡安瑞李博文陶飞
Owner BEIHANG UNIV
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