A Novel Contextual Information Recommendation Model and Its Application in e-Commerce Customer Satisfaction Management
In the current supply chain environment, distributed cognition theory tells us that various types of context information in which a recommendation is provided are important for e-commerce customer satisfaction management. However, traditional recommendation model does not consider the distributed an...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2015/691781 |
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| _version_ | 1832559352368594944 |
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| author | Feipeng Guo Qibei Lu |
| author_facet | Feipeng Guo Qibei Lu |
| author_sort | Feipeng Guo |
| collection | DOAJ |
| description | In the current supply chain environment, distributed cognition theory tells us that various types of context information in which a recommendation is provided are important for e-commerce customer satisfaction management. However, traditional recommendation model does not consider the distributed and differentiated impact of different contexts on user needs, and it also lacks adaptive capacity of contextual recommendation service. Thus, a contextual information recommendation model based on distributed cognition theory is proposed. Firstly, the model analyzes the differential impact of various sensitive contexts and specific examples on user interest and designs a user interest extraction algorithm based on distributed cognition theory. Then, the sensitive contexts extracted from user are introduced into the process of collaborative filtering recommendation. The model calculates similarity among user interests. Finally, a novel collaborative filtering algorithm integrating with context and user similarity is designed. The experimental results in e-commerce and benchmark dataset show that this model has a good ability to extract user interest and has higher recommendation accuracy compared with other methods. |
| format | Article |
| id | doaj-art-68a9f56ec86c4896a6ee0694cfd6b5df |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-68a9f56ec86c4896a6ee0694cfd6b5df2025-02-03T01:30:13ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2015-01-01201510.1155/2015/691781691781A Novel Contextual Information Recommendation Model and Its Application in e-Commerce Customer Satisfaction ManagementFeipeng Guo0Qibei Lu1Department of Information Technology, Zhejiang Economic and Trade Polytechnic, Hangzhou 310018, ChinaSchool of Economics and Trade, Taizhou Vocational and Technical College, Taizhou 318000, ChinaIn the current supply chain environment, distributed cognition theory tells us that various types of context information in which a recommendation is provided are important for e-commerce customer satisfaction management. However, traditional recommendation model does not consider the distributed and differentiated impact of different contexts on user needs, and it also lacks adaptive capacity of contextual recommendation service. Thus, a contextual information recommendation model based on distributed cognition theory is proposed. Firstly, the model analyzes the differential impact of various sensitive contexts and specific examples on user interest and designs a user interest extraction algorithm based on distributed cognition theory. Then, the sensitive contexts extracted from user are introduced into the process of collaborative filtering recommendation. The model calculates similarity among user interests. Finally, a novel collaborative filtering algorithm integrating with context and user similarity is designed. The experimental results in e-commerce and benchmark dataset show that this model has a good ability to extract user interest and has higher recommendation accuracy compared with other methods.http://dx.doi.org/10.1155/2015/691781 |
| spellingShingle | Feipeng Guo Qibei Lu A Novel Contextual Information Recommendation Model and Its Application in e-Commerce Customer Satisfaction Management Discrete Dynamics in Nature and Society |
| title | A Novel Contextual Information Recommendation Model and Its Application in e-Commerce Customer Satisfaction Management |
| title_full | A Novel Contextual Information Recommendation Model and Its Application in e-Commerce Customer Satisfaction Management |
| title_fullStr | A Novel Contextual Information Recommendation Model and Its Application in e-Commerce Customer Satisfaction Management |
| title_full_unstemmed | A Novel Contextual Information Recommendation Model and Its Application in e-Commerce Customer Satisfaction Management |
| title_short | A Novel Contextual Information Recommendation Model and Its Application in e-Commerce Customer Satisfaction Management |
| title_sort | novel contextual information recommendation model and its application in e commerce customer satisfaction management |
| url | http://dx.doi.org/10.1155/2015/691781 |
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