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Determining Text Databases to Search in the Internet.

Weiyi Meng, King-Lup Liu, Clement T. Yu, Xiaodong Wang, Yuhsi Chang, Naphtali Rishe: Determining Text Databases to Search in the Internet. VLDB 1998: 14-25
@inproceedings{DBLP:conf/vldb/MengLYWCR98,
  author    = {Weiyi Meng and
               King-Lup Liu and
               Clement T. Yu and
               Xiaodong Wang and
               Yuhsi Chang and
               Naphtali Rishe},
  editor    = {Ashish Gupta and
               Oded Shmueli and
               Jennifer Widom},
  title     = {Determining Text Databases to Search in the Internet},
  booktitle = {VLDB'98, Proceedings of 24rd International Conference on Very
               Large Data Bases, August 24-27, 1998, New York City, New York,
               USA},
  publisher = {Morgan Kaufmann},
  year      = {1998},
  isbn      = {1-55860-566-5},
  pages     = {14-25},
  ee        = {db/conf/vldb/MengLYWCR98.html},
  crossref  = {DBLP:conf/vldb/98},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

Text data in the Internet can be partitioned into many databases naturally. Efficient retrieval of desired data can be achieved if we can accuratelypredict the usefulness of each database, because with such information, weonly need to retrieve potentially useful documents from useful databases. In this paper, we propose two new methods for estimating the usefulness oftext databases. For a given query, the usefulness of a text database in this paper is defined to be the number of documents in the database that aresufficiently similar to the query. Such a usefulness measure enables naive-users to make informed decision about which databases to search. We also consider the collection fusion problem. Because local databases may employsimilarity functions that are different from that used by the global database, the threshold used by a local database to determine whether a document is potentially useful may be different from that used by the global database. We provide techniques that determine the best threshold for a given local database.

Copyright © 1998 by the VLDB Endowment. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.

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Printed Edition

Ashish Gupta, Oded Shmueli, Jennifer Widom (Eds.): VLDB'98, Proceedings of 24rd International Conference on Very Large Data Bases, August 24-27, 1998, New York City, New York, USA. Morgan Kaufmann 1998, ISBN 1-55860-566-5
Contents BibTeX

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Referenced by

  1. Surajit Chaudhuri, Luis Gravano: Evaluating Top-k Selection Queries. VLDB 1999: 397-410
  2. Weiyi Meng, King-Lup Liu, Clement T. Yu, Wensheng Wu, Naphtali Rishe: Estimating the Usefulness of Search Engines. ICDE 1999: 146-153
  3. Yong S. Choi, Suk I. Yoo: Neural Net Agent for Discovering Text Databases on the Web. ADBIS (Short Papers) 1999: 221-231
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