Research on Personalized Recommender System Adapting to Different Business
The rapid development of internet technology, especially the developed of Web 2.0 which has the main feature of personality, making a lot of information in front of people at the same time. The value of personalized recommendation technology has become increasingly prominent. A design of personalize...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2014-08-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.3969/j.issn.1000-0801.2014.08.019/ |
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| _version_ | 1841529364712259584 |
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| author | Caixia Tao Hai Yuan Kang Chen Anhua Ma |
| author_facet | Caixia Tao Hai Yuan Kang Chen Anhua Ma |
| author_sort | Caixia Tao |
| collection | DOAJ |
| description | The rapid development of internet technology, especially the developed of Web 2.0 which has the main feature of personality, making a lot of information in front of people at the same time. The value of personalized recommendation technology has become increasingly prominent. A design of personalized recommender system adapting to different business was presented, including the collection and analysis of user's all explicit and implicit behavior, using user behavior profiles and entropy method to determine the weight of the behavior for analyzing user interest, the introduction of time forgetting function to solve the problem of user interest drift, and getting a list of the user's personalized recommendation based on collaborative filtering technology. Finally, the system test assessment analysis based on the actual data was provided. |
| format | Article |
| id | doaj-art-c3147a66398749fa8d85ab1a4d00828f |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2014-08-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-c3147a66398749fa8d85ab1a4d00828f2025-01-15T03:19:26ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012014-08-013013113559620818Research on Personalized Recommender System Adapting to Different BusinessCaixia TaoHai YuanKang ChenAnhua MaThe rapid development of internet technology, especially the developed of Web 2.0 which has the main feature of personality, making a lot of information in front of people at the same time. The value of personalized recommendation technology has become increasingly prominent. A design of personalized recommender system adapting to different business was presented, including the collection and analysis of user's all explicit and implicit behavior, using user behavior profiles and entropy method to determine the weight of the behavior for analyzing user interest, the introduction of time forgetting function to solve the problem of user interest drift, and getting a list of the user's personalized recommendation based on collaborative filtering technology. Finally, the system test assessment analysis based on the actual data was provided.http://www.telecomsci.com/zh/article/doi/10.3969/j.issn.1000-0801.2014.08.019/personalized recommender systemuser interest analysisentropyinterest driftcollaborative filtering |
| spellingShingle | Caixia Tao Hai Yuan Kang Chen Anhua Ma Research on Personalized Recommender System Adapting to Different Business Dianxin kexue personalized recommender system user interest analysis entropy interest drift collaborative filtering |
| title | Research on Personalized Recommender System Adapting to Different Business |
| title_full | Research on Personalized Recommender System Adapting to Different Business |
| title_fullStr | Research on Personalized Recommender System Adapting to Different Business |
| title_full_unstemmed | Research on Personalized Recommender System Adapting to Different Business |
| title_short | Research on Personalized Recommender System Adapting to Different Business |
| title_sort | research on personalized recommender system adapting to different business |
| topic | personalized recommender system user interest analysis entropy interest drift collaborative filtering |
| url | http://www.telecomsci.com/zh/article/doi/10.3969/j.issn.1000-0801.2014.08.019/ |
| work_keys_str_mv | AT caixiatao researchonpersonalizedrecommendersystemadaptingtodifferentbusiness AT haiyuan researchonpersonalizedrecommendersystemadaptingtodifferentbusiness AT kangchen researchonpersonalizedrecommendersystemadaptingtodifferentbusiness AT anhuama researchonpersonalizedrecommendersystemadaptingtodifferentbusiness |