DocumentCode :
1195262
Title :
Comparison of three vertical search spiders
Author :
Chau, Michael ; Chen, Hsinchun
Author_Institution :
Dept. of Manage. Inf. Syst., Arizona Univ., Tucson, AZ, USA
Volume :
36
Issue :
5
fYear :
2003
fDate :
5/1/2003 12:00:00 AM
Firstpage :
56
Lastpage :
62
Abstract :
The Web´s dynamic, unstructured nature makes locating resources difficult. Vertical search engines solve part of the problem by keeping indexes only in specific domains. They also offer more opportunity to apply domain knowledge in the spider applications that collect content for their databases. The authors used three approaches to investigate algorithms for improving the performance of vertical search engine spiders: a breadth-first graph-traversal algorithm with no heuristics to refine the search process, a best-first traversal algorithm that uses a hyperlink-analysis heuristic, and a spreading-activation algorithm based on modeling the Web as a neural network.
Keywords :
Web design; hypermedia; information retrieval system evaluation; neural nets; search engines; tree searching; Web modeling; best-first traversal algorithm; breadth-first graph-traversal algorithm; hyperlink-analysis heuristic; neural network; performance; search engines; spreading-activation algorithm; vertical search spiders; Cancer; HTML; Information analysis; Iterative algorithms; Joining processes; Lungs; Search engines; Terminology; Uniform resource locators; Web pages;
fLanguage :
English
Journal_Title :
Computer
Publisher :
ieee
ISSN :
0018-9162
Type :
jour
DOI :
10.1109/MC.2003.1198237
Filename :
1198237
Link To Document :
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