Service recommendation method oriented to service supply chain network

A service recommendation and service-oriented technology, applied in the field of supply chain configuration, can solve problems such as inability to find similar users or similar items, cold start, data sparsity, etc.

Active Publication Date: 2014-11-26
ZHEJIANG UNIV OF FINANCE & ECONOMICS
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the recommendation effect of collaborative filtering technology is easily affected by data sparsity and cold start problem.
When historical data is insufficient to find similar users or item

Method used

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  • Service recommendation method oriented to service supply chain network
  • Service recommendation method oriented to service supply chain network
  • Service recommendation method oriented to service supply chain network

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Embodiment Construction

[0055] The technical solution of the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments, and the following embodiments do not constitute a limitation of the present invention.

[0056] The present invention is based on figure 1 As shown in the service supply chain network, a service recommendation method for service supply chain network is proposed. in such as figure 1 In the service supply chain network shown, it is assumed that each node represents a user or a manufacturing service, including the user node U 1 ~ U 4 and service node S 5 ~S 10 , each link represents the interaction relationship between nodes. This embodiment takes the manufacturing service as an example for illustration, but it is not limited to the manufacturing service, and will not be described in detail below.

[0057] Based on the above-mentioned service supply chain network, a service recommendation method oriented to the servi...

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Abstract

The invention discloses a service recommendation method oriented to a service supply chain network. The method includes the steps that firstly, a transfer matrix is established according to the linkage relationship among all nodes in the service supply chain network, and credit values of all the nodes are calculated according to the transfer matrix; then, similarity of credit enhancement between every two nodes is calculated, and neighbors of all the nodes are established; finally, for users needing service recommendation, the service quality evaluation values of services needed by the users are predicted according to the neighbors of the corresponding nodes, and the services with high service quality evaluation values are recommended to the users. By the adoption of the service recommendation method, the service quality evaluation values of the services needed by the users can also be successfully predicted even when historical data are insufficient or the historical data of part of the nodes do not exist, the problems of data sparsity and cold boot in the existing collaborative filtering technology are solved, and service recommendation accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of supply chain configuration, and in particular relates to a service recommendation method oriented to a service supply chain network. Background technique [0002] In the field of supply chain configuration, it is generally believed that its development trend is to increasingly emphasize the sharing and integration of various external high-quality services (such as resources and knowledge). The exponential growth of the Internet and the accelerated globalization of manufacturing enterprises have significantly affected the interoperability of cross-enterprise collaboration services. For example, the SOA architecture and the corresponding Web services not only provide a dynamic implementation for the communication between manufacturing enterprises and their partners (including suppliers and customers) through the seamless integration of various complex distributed manufacturing resources and knowledge techn...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q50/04
CPCY02P90/30G06F16/9535G06Q50/04
Inventor 张文宇张帅
Owner ZHEJIANG UNIV OF FINANCE & ECONOMICS
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