CubeSVD: a novel approach to personalized Web search

As the competition of Web search market increases, there is a high demand for personalized Web search to conduct retrieval incorporating Web users' information needs. This paper focuses on utilizing clickthrough data to improve Web search. Since millions of searches are conducted everyday, a search engine accumulates a large volume of clickthrough data, which records who submits queries and which pages he/she clicks on. The clickthrough data is highly sparse and contains different types of objects (user, query and Web page), and the relationships among these objects are also very complicated. By performing analysis on these data, we attempt to discover Web users' interests and the patterns that users locate information. In this paper, a novel approach CubeSVD is proposed to improve Web search. The clickthrough data is represented by a 3-order tensor, on which we perform 3-mode analysis using the higher-order singular value decomposition technique to automatically capture the...

• Type: Conference
• Year: 2005
• Where: WWW
• Authors: Jian-Tao Sun, Hua-Jun Zeng, Huan Liu, Yuchang Lu, Zheng Chen
• Keywords: Clickthrough Data, Internet Technology, Web Search, Web Search Market, WWW 2005