Improved Recommendations Based on Trust Relationships in Social Networks
In order to alleviate the pressure of information overload and enhance consumer satisfaction, personalization recommendation has become increasingly popular in recent years. As a result, various approaches for recommendation have been proposed in the past few years. However, traditional recommendati...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2017-03-01
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| Series: | Future Internet |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1999-5903/9/1/9 |
| _version_ | 1818940957877338112 |
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| author | Hao Tian Peifeng Liang |
| author_facet | Hao Tian Peifeng Liang |
| author_sort | Hao Tian |
| collection | DOAJ |
| description | In order to alleviate the pressure of information overload and enhance consumer satisfaction, personalization recommendation has become increasingly popular in recent years. As a result, various approaches for recommendation have been proposed in the past few years. However, traditional recommendation methods are still troubled with typical issues such as cold start, sparsity, and low accuracy. To address these problems, this paper proposed an improved recommendation method based on trust relationships in social networks to improve the performance of recommendations. In particular, we define trust relationship afresh and consider several representative factors in the formalization of trust relationships. To verify the proposed approach comprehensively, this paper conducted experiments in three ways. The experimental results show that our proposed approach leads to a substantial increase in prediction accuracy and is very helpful in dealing with cold start and sparsity. |
| first_indexed | 2024-12-20T06:47:54Z |
| format | Article |
| id | doaj.art-0c910072872149f3867a6348f71b4faf |
| institution | Directory Open Access Journal |
| issn | 1999-5903 |
| language | English |
| last_indexed | 2024-12-20T06:47:54Z |
| publishDate | 2017-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj.art-0c910072872149f3867a6348f71b4faf2022-12-21T19:49:39ZengMDPI AGFuture Internet1999-59032017-03-0191910.3390/fi9010009fi9010009Improved Recommendations Based on Trust Relationships in Social NetworksHao Tian0Peifeng Liang1School of Information Engineering, Hubei University of Economics, No. 8, Yangqiaohu Ave., Jiangxia Dist., Wuhan 430205, ChinaGraduate School of Information, Production and Systems, Waseda University, Hibikino 2–7, Wakamatsu-ku, Kitakyushu 808-0135, JapanIn order to alleviate the pressure of information overload and enhance consumer satisfaction, personalization recommendation has become increasingly popular in recent years. As a result, various approaches for recommendation have been proposed in the past few years. However, traditional recommendation methods are still troubled with typical issues such as cold start, sparsity, and low accuracy. To address these problems, this paper proposed an improved recommendation method based on trust relationships in social networks to improve the performance of recommendations. In particular, we define trust relationship afresh and consider several representative factors in the formalization of trust relationships. To verify the proposed approach comprehensively, this paper conducted experiments in three ways. The experimental results show that our proposed approach leads to a substantial increase in prediction accuracy and is very helpful in dealing with cold start and sparsity.http://www.mdpi.com/1999-5903/9/1/9recommendationtrust relationshipaccuracycold startsparsity |
| spellingShingle | Hao Tian Peifeng Liang Improved Recommendations Based on Trust Relationships in Social Networks Future Internet recommendation trust relationship accuracy cold start sparsity |
| title | Improved Recommendations Based on Trust Relationships in Social Networks |
| title_full | Improved Recommendations Based on Trust Relationships in Social Networks |
| title_fullStr | Improved Recommendations Based on Trust Relationships in Social Networks |
| title_full_unstemmed | Improved Recommendations Based on Trust Relationships in Social Networks |
| title_short | Improved Recommendations Based on Trust Relationships in Social Networks |
| title_sort | improved recommendations based on trust relationships in social networks |
| topic | recommendation trust relationship accuracy cold start sparsity |
| url | http://www.mdpi.com/1999-5903/9/1/9 |
| work_keys_str_mv | AT haotian improvedrecommendationsbasedontrustrelationshipsinsocialnetworks AT peifengliang improvedrecommendationsbasedontrustrelationshipsinsocialnetworks |