An Optimized Collaborative Filtering Method to Construct Spatial-temporal Behavior Pattern-based User Interest Model
An Optimized Collaborative Filtering Method to Construct Spatial-temporal Behavior Pattern-based User Interest Model
复制标题
一种构建基于时空行为模式的用户兴趣模型的优化协同过滤方法
DOI：
10.1002/tee.22369
复制
发表时间：
2017
影响因子：
1
通讯作者：
Yang Yang
中科院分区：
文献类型：
--
作者：
Cheng Jiujun;Hu Liufei;Gao Shangce;Liu Junjun;Yang Yang
移动的社交网络（MSN）具有真实的时间性、移动性和社会关系性，提供了更真实的时间性、维度和异构性更强的元数据。由于这些固有的特点，传统的用户兴趣模型不能很好地反映移动的用户的兴趣。本文旨在联合收割机恰当地结合移动的社交网络的特点，建立一个有效表示用户兴趣的用户兴趣模型。该模型能够过滤用户不感兴趣的信息，提供个性化的移动的服务，解决信息过载问题，获得良好的用户体验。为了实现这些，首先，我们探讨了传统的用户兴趣模型的各种问题，并分析了使用传统的模型来表示移动的用户兴趣的众多问题。然后提出了一种结合移动的个性化属性和上下文信息的用户时空行为模式，然后提出了一种表示用户兴趣的用户兴趣模型。其次，提出了一种基于用户和主题的混合协同过滤方法，综合考虑用户兴趣广泛度、主题流行度以及用户影响力，计算用户兴趣并建立用户兴趣模型。最后，提出了一种基于用户时空行为模式的模型构建算法。实验结果表明，该模型能有效地表示移动的社交网络下的用户兴趣。通过综合考虑用户兴趣广泛度、主题流行度和用户影响力，验证了构建算法的适应性和准确性得到显著提高。© 2016日本电气工程师协会。由John Wiley & Sons公司出版
Mobile social network (MSN) has properties of real time, mobility, and social relationship, and provides more real‐time, more dimensional, and more heterogeneous metadata. The traditional user interest models represent mobile users' interests unsatisfactorily because of these inherent characteristics. This paper aims to combine the characteristics of mobile social networks appropriately to build a user interest model effectively for representing user interests. The constructed model is supposed to enable users to filter uninterested information, to provide personalized mobile service, to solve information overload, and to gain a good user experience. In order to realize these, first, we explore various issues of the traditional user interest model, and analyze the numerous problems in using traditional models to represent mobile user interests. Then a user spatial‐temporal behavior pattern in conjunction with mobile personalization attributes and context information is proposed, which is followed by a proposal of a user interest model to represent user interests. Second, we introduce a hybrid collaborative filtering method based on users and subjects to calculate user interests and to build the user interest model, considering the user interest extensive degree, the subject popularity, as well as the user influence. Finally, a model construction algorithm is proposed based on the user's spatial‐temporal behavior pattern. Experimental results show that the proposed model can represent user interests effectively under the mobile social network. Furthermore, it is verified that the adaptability and accuracy of the construction algorithm are significantly improved by considering the user interest extensive degree, the subject popularity, and the user influence. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.