WWW2006 - CWS: A Comparative Web Search System
| Skip to main content | Skip to navigation |

Register Now!

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:

Presentation Slides:

Track: Search

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.

Citation

Sun, J., Wang, X., Shen, D., Zeng, H., and Chen, Z. 2006. CWS: a comparative web search system. In Proceedings of the 15th International Conference on World Wide Web (Edinburgh, Scotland, May 23 - 26, 2006). WWW '06. ACM Press, New York, NY, 467-476.
DOI= http://doi.acm.org/10.1145/1135777.1135846

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)

Organised by

ECS Logo

in association with

BCS Logo ACM Logo

Platinum Sponsors

Sponsor of The CIO Dinner


Become a sponsor or exhibitor
Valid XHTML 1.0! IFIP logo WWW Conference Committee logo Web Consortium logo Valid CSS!