| 融合情境关系的社会化媒体用户兴趣推荐 |
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| 引用本文： | 房小可,严承希.融合情境关系的社会化媒体用户兴趣推荐[J].图书情报工作,2017,61(21):99-105. |
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| 作者姓名： | 房小可 严承希 |
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| 作者单位： | 1. 北京联合大学应用文理学院 北京 100191;
2. 北京大学信息管理系 北京 100871 |
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| 基金项目： | 本文系北京联合大学新起点项目"社会化媒体环境下用户需求的细粒度挖掘研究"（项目编号：Sk10201617）研究成果之一。 |
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| 摘 要： | 目的/意义]用户兴趣推荐是信息服务中的重要内容,针对目前融合情境信息推荐的研究更多是直接将情境作为单因素而缺乏考虑情境关联的思想,本文以情境关系为切入点实现社会化媒体用户的兴趣推荐。方法/过程]以具有相似情境用户可能具有相似兴趣为假设,来改进用户原始兴趣网络从而实现推荐。通过社会网络和资源相似性计算构建原始兴趣网络中显性网络和隐性网络;借鉴共现原理和情境本身相似性构建情境网络;通过兴趣传递关系计算直接兴趣度与间接兴趣度;最后借鉴协同过滤的思想实现推荐。结果/结论]与以往的只考虑单一情境因素的推荐方法相比,基于本方法的实验表明,将情境关系融入到推荐过程中不仅可以扩展用户的社会关系,而且可以得到更好的推荐效果。
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| 关 键 词： | 情境关系 社会化媒体 兴趣推荐 |
| 收稿时间： | 2017-04-06 |
User Interest Recommendation by Combining Contextual Relations on the Social Media |
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| Fang Xiaoke,Yan Chengxi.User Interest Recommendation by Combining Contextual Relations on the Social Media[J].Library and Information Service,2017,61(21):99-105. |
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| Authors: | Fang Xiaoke Yan Chengxi |
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| Institution: | 1. College of Applied Arts and Science, Beijing Union University, Beijing 100191;
2. Department of Information Management, Peking University, Beijing 100871 |
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| Abstract: | Purpose/significance] User interest recommendation is an important content in information services. The context of current researches about information recommendation is considered as an independent factor but ignoring the relation in it. This paper combined the contextual relations into the recommending process and realized the user interest recommendation on the social media. Method/process] This paper takes a hypothesis that users in the similar context may have similar interests to improve the original user interest network and achieve the recommendation:constructing the explicit and implicit network by the social network and the resources similarity; constructing the contextual network by the co-occurrence principle and the context similarity itself; calculating direct interest scores and indirect interest scores by the network transmission; realizing recommendation by using collaborative filtering. Result/conclusion] The experiment shows that combing contextual relations into the recommendation process can not only expand users' social relationship, but also ameliorate recommendation results. |
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| Keywords: | contextual relation social media interest recommendation |
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