Abstract
In this paper we study the problem of searching the Web with online learning algorithms. We consider that Web documents can be represented by vectors of n boolean attributes. A search engine is viewed as a learner, and a user is viewed as a teacher. We investigate the number of queries a search engine needs from the user to search for a collection of Web documents. We design several efficient learning algorithms to search for any collection of documents represented by a disjunction (or a conjunction) of relevant attributes with the help of membership queries or equivalence queries.
Similar content being viewed by others
References
D. Angluin. Queries and concept learning, Machine Learning 2, 319–342, 1988.
C. M. Bowman, P. B. Danzig, D. R. Hardy, U. Manber, M. F. Schwartz. The harvest information discovery and access system, Proceedings of the Second International World Wide Web Conference, 1994, pp. 763-771.
O. Etzioni. The World-Wide Web: Quagmire or gold mine? Communication of ACM 39, 65–68, 1997.
S. Lawrence, C. L. Giles. Search the World Wide Web, Science 280, 98–100, 1998.
N. Littlestone. Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm, Machine Learning 2, 285–318, 1988.
X. Meng, Z. Chen. Personalize web search using information on client’s side, Proceedings of the Fifth International Conference of Young Computer Scientists, in press, Nanjing, China, au]gust 17–20, 1999.
G. Salton. au]tomatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer, Addison Wesley, Reading, MA, 1989.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chen, Z., Meng, X. & Fowler, R.H. Searching the Web with Queries. Knowledge and Information Systems 1, 369–375 (1999). https://doi.org/10.1007/BF03325104
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/BF03325104