CWS: A Comparative Web Search System

• Jian-Tao Sun, Microsoft Research Asia, P.R. China
• Xuanhui Wang, Department of Computer Science, University of Illinois at Urbana-Champaign, USA
• Dou Shen, Department of Computer Science, Hong Kong University of Science and Technology, P.R. China
• Hua-Jun Zeng, Microsoft Research Asia, P.R. China
• Zheng Chen, Microsoft Research Asia, P.R. China

Full text:

Track: Search

Slot: 16:00-17:30, Thursday 25th May

In this paper, we define and study a novel search problem: Comparative Web Search (CWS). The task of CWS is to seek relevant and comparative information from the Web to help users conduct comparisons among a set of topics. A system called CWS is developed to effectively facilitate Web users' comparison needs. Given a set of queries, which represent the topics that a user wants to compare, the system is characterized by: (1) automatic retrieval and ranking of Web pages by incorporating both their relevance to the queries and the comparative contents they contain; (2) automatic clustering of the comparative contents into semantically meaningful themes; (3) extraction of representative keyphrases to summarize the commonness and differences of the comparative contents in each theme. We developed a novel interface which supports two types of view modes: a pair-view which displays the result in the page level, and a cluster-view which organizes the comparative pages into the themes and displays the extracted phrases to facilitate users' comparison. Experiment results show the CWS system is effective and efficient.

Other items being presented by these speakers

• Mining Clickthrough Data for Collaborative Web Search (Posters Track)
• A Comparison of Implicit and Explicit Links for Web Page Classification (Data Mining Track)