Abstract
With the explosion of the Internet, search engines are more and more popular. Up to now, most of the search engines will provide the same results to the different users on the same query. However, users may have their own sense of the same query and need personalized results. Also users are often not satisfied with the results primitively returned and need some mechanism for refining the results. In this work, we propose an on-line text distinguishers collection method under an interactive meta search framework. We also use those distinguishers to re-rank the search results to achieve the specific ranking order. Text distinguishers are defined as those words which can separate one document from others. They can be used to reflect the user’s preference for a specific query.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
E. Selberg, and O. Etzioni: The MetaCrawler Architecture for Resource Aggregation on the Web, IEEE Expert, January/February 1997.
O. Zamir and O. Etzioni. Grouper: A Dynamic Clustering Interface to Web Search Results. Proc. of WWW8. Toronto Canada 1999.
Krishna Bharat: SearchPad Explicit Capture of Search Context to Support Web Search. Proc. of WWW9. Amsterdam Holand. 2000.
Lev Finkelstein and Evgeniy Gabrilovich and Yossi Matias etc.: Placing Search in Context: The Concept Revisited. Proc. of WWW10. HongKong. 2001.
Zonghuan Wu, Weiyi Meng, Clement Yu, Zhuogang Li: Towards a Highly-Scalable and Effective Metasearch Engine. Proc. of WWW10. HongKong. 2001.
G. Salton: The SMART Retrieval System-Experiments in Automatic Ducument Processing. Prentice Hall Inc. Englewood Cliffs NJ. 1971.
D. Dreilinger: Experiences with Selecting Search Engines Using Metasearch. ACM TOIS. 15(3). July 1997. pp. 195–222.
Wai-Chiu Wong, Ada Wai-chee Fu: Incremental Document Clustering for Web Page Classification. Proc. of 2000 International Conference on Information Society in the 21st Century. Fukushima Japan. 2000.
T. Joachims, Dayne Freitag, Tom Mitchell: WebWatcher: A Tour Guide for the World Wide Web. Proc of IJCAI97. 1997.
Jay Budzik, Kristian J. Hammond: User Interactions with Everyday Applications as Context for Just-in-time Information Access. Proc of IUI2000. 2000
L. Chen and K. Sycara: Webmate: A personal agent for browsing and searching. Proc. of 2nd International Conference on Autonomous Agents 1998
Marko Balabanovic and Yoav Shoham. Fab: Contentbased Collaborative Recommendation. Communications of the ACM, 40(3):66–72, March 1997.
Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl: Item-based Collaborative Filtering Recommendation Algorithms. Proc. of WWW10 HongKong. 2001
William W. Cohen, Wei Fan: Web-Collaborative Filtering: Recommending Music by Crawling The Web. Proc. of WWW9. Amsterdam Holand. 2000
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, K., Zheng, W., Deng, X., Feng, H., Zhu, S. (2002). Text Distinguishers Used in an Interactive Meta Search Engine. In: Meng, X., Su, J., Wang, Y. (eds) Advances in Web-Age Information Management. WAIM 2002. Lecture Notes in Computer Science, vol 2419. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45703-8_17
Download citation
DOI: https://doi.org/10.1007/3-540-45703-8_17
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44045-1
Online ISBN: 978-3-540-45703-9
eBook Packages: Springer Book Archive