基于位置簇的移动生活服务个性化推荐技术

doi:10.11772/j.issn.1001-9081.2015.04.1148

计算机应用 ›› 2015, Vol. 35 ›› Issue (4): 1148-1153.DOI: 10.11772/j.issn.1001-9081.2015.04.1148

基于位置簇的移动生活服务个性化推荐技术

郑慧, 李冰, 陈冬林, 刘平峰

武汉理工大学电子商务与智能服务研究中心, 武汉 430070

收稿日期:2014-11-17 修回日期:2015-01-13 出版日期:2015-04-10 发布日期:2015-04-08
通讯作者: 郑慧
作者简介:郑慧(1991-),女,湖北襄阳人,硕士研究生,主要研究方向:电子商务智能推荐、数据挖掘; 李冰(1983-),女,吉林通化人,副教授,博士,主要研究方向:模式识别、数据挖掘、复杂网络; 陈冬林(1970-),男,湖北武汉人,教授, 博士,主要研究方向: 电子商务智能推荐、语义网、网格; 刘平峰(1972-),男,湖北武汉人,副教授,博士,主要研究方向:电子商务、语义网、知识工程。
基金资助:
国家科技支撑计划项目(2012BAH93F04)。

Personalized recommendation technique for mobile life services based on location cluster

ZHENG Hui, LI Bing, CHEN Donglin, LIU Pingfeng

Research Center for E-business and Intelligent Services, Wuhan University of Technology, Wuhan Hubei 430070, China

Received:2014-11-17 Revised:2015-01-13 Online:2015-04-10 Published:2015-04-08

摘要/Abstract

摘要：

当前的移动推荐系统只将位置信息作为推荐属性处理,弱化了其在推荐中所起的作用,更重要的是忽略了移动生活服务位置相关性和用户空间运动有界性特征。针对该问题,设计了基于位置簇的用户偏好表示模型和移动生活服务个性化推荐算法。该算法通过模糊聚类得到位置簇,使用遗忘因子调节用户在该位置簇对服务资源属性值的偏好,并且采用概率分布和信息熵理论计算属性权重,按位置簇对用户偏好和服务资源进行匹配得到top-N推荐集。由于位置簇的定义,使得算法给出与用户偏好相似度较高的服务资源。案例分析结果符合这一结论,从而验证了算法的有效性和精确性。

关键词: 移动生活服务, 位置簇, 模糊聚类, 用户偏好, 个性化推荐

Abstract:

Current mobile recommendation systems limit the real role of location information, because the systems just take location as a general property. More importantly, the correlation of location and the boundary of activities of users have been ignored. According to this issue, personalized recommendation technique for mobile life services based on location cluster was proposed, which considered both user preference in its location cluster and the related weight by forgetting factor and information entropy. It used fuzzy cluster to get the location cluster, then used forgetting factor to adjust the preference of the service resources in the location cluster. Then the related weight was obtained by using probability distribution and information entropy. The top-N recommendation set was got by matching the user preference and service resources. As a result, the algorithm can provide service resources with high similarities with user preference. This conclusion has been verified by case study.

Key words: mobile life service, location cluster, fuzzy clustering, user preference, personalized recommendation

中图分类号:

TP391

郑慧, 李冰, 陈冬林, 刘平峰. 基于位置簇的移动生活服务个性化推荐技术[J]. 计算机应用, 2015, 35(4): 1148-1153.

ZHENG Hui, LI Bing, CHEN Donglin, LIU Pingfeng. Personalized recommendation technique for mobile life services based on location cluster[J]. Journal of Computer Applications, 2015, 35(4): 1148-1153.

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基于位置簇的移动生活服务个性化推荐技术

Personalized recommendation technique for mobile life services based on location cluster

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