Researcb on Social Network Collaborative Filtering Based E-commerce Recommending
With the development of the social network relation, whether the recommendation is successful, is not only depending on the characteristics of goods, but also influenced by social network relationship. Many users more trust from their friends'recommendation, rather than the machine recommended...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2014-09-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.3969／j.issn.1000-0801.2014.09.011/ |
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| _version_ | 1841529314576695296 |
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| author | Chunhua Ju Fuguang Bao Chonghuan Xu |
| author_facet | Chunhua Ju Fuguang Bao Chonghuan Xu |
| author_sort | Chunhua Ju |
| collection | DOAJ |
| description | With the development of the social network relation, whether the recommendation is successful, is not only depending on the characteristics of goods, but also influenced by social network relationship. Many users more trust from their friends'recommendation, rather than the machine recommended by single factor calculated results. Therefore, an E-commerce recommending system based on social network collaborative filtering was proposed. In the system, the crucial factors of social network relation intensity, interest preference intensity and production popularity with reputation intensity were set.And each first-level factor was composed of some second-level factors.Experimental results verify that social network relationships will affect users shopping behaviors and so on. In addition, the recommendation method based on social network is superior to other approaches and has better application effect. |
| format | Article |
| id | doaj-art-223eec1b9e2841b095d6850192ae404f |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2014-09-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-223eec1b9e2841b095d6850192ae404f2025-01-15T03:18:57ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012014-09-0130828659619537Researcb on Social Network Collaborative Filtering Based E-commerce RecommendingChunhua JuFuguang BaoChonghuan XuWith the development of the social network relation, whether the recommendation is successful, is not only depending on the characteristics of goods, but also influenced by social network relationship. Many users more trust from their friends'recommendation, rather than the machine recommended by single factor calculated results. Therefore, an E-commerce recommending system based on social network collaborative filtering was proposed. In the system, the crucial factors of social network relation intensity, interest preference intensity and production popularity with reputation intensity were set.And each first-level factor was composed of some second-level factors.Experimental results verify that social network relationships will affect users shopping behaviors and so on. In addition, the recommendation method based on social network is superior to other approaches and has better application effect.http://www.telecomsci.com/zh/article/doi/10.3969／j.issn.1000-0801.2014.09.011/social network relation intensityinterest preference intensityreputation intensityAHPcollaborativefiltering |
| spellingShingle | Chunhua Ju Fuguang Bao Chonghuan Xu Researcb on Social Network Collaborative Filtering Based E-commerce Recommending Dianxin kexue social network relation intensity interest preference intensity reputation intensity AHP collaborative filtering |
| title | Researcb on Social Network Collaborative Filtering Based E-commerce Recommending |
| title_full | Researcb on Social Network Collaborative Filtering Based E-commerce Recommending |
| title_fullStr | Researcb on Social Network Collaborative Filtering Based E-commerce Recommending |
| title_full_unstemmed | Researcb on Social Network Collaborative Filtering Based E-commerce Recommending |
| title_short | Researcb on Social Network Collaborative Filtering Based E-commerce Recommending |
| title_sort | researcb on social network collaborative filtering based e commerce recommending |
| topic | social network relation intensity interest preference intensity reputation intensity AHP collaborative filtering |
| url | http://www.telecomsci.com/zh/article/doi/10.3969／j.issn.1000-0801.2014.09.011/ |
| work_keys_str_mv | AT chunhuaju researcbonsocialnetworkcollaborativefilteringbasedecommercerecommending AT fuguangbao researcbonsocialnetworkcollaborativefilteringbasedecommercerecommending AT chonghuanxu researcbonsocialnetworkcollaborativefilteringbasedecommercerecommending |