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Proceedings Paper

Buddy: fusing multiple search results together
Author(s): John J. Salerno; Doug M. Boulware; John E. Myers; Vishal Khattri; Dave R. Corzillus
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Paper Abstract

If you have ever used a popular search engine on the Internet to search for a specific topic you are interested in, you know that most of the results you get back are unrelated, or do not have the information for which you are searching. Usually you end up looking through many Web pages before you find information. Different search engines give you different ranked results, so how do you choose which one to use? Buddy solves these problems for you. With Buddy you can search multiple search engines with many different queries. Using topic trees to create in depth search queries, utilizing the power of many renowned search engines, with the ability to dynamically create and delete them on the fly, Buddy gives you the results you want on the information you are looking for. Using its unique ranking algorithm the results from multiple search engines are correlated and fused together, removing multiple document hits. This paper will discuss the motivation for and the capabilities of Buddy.

Paper Details

Date Published: 21 March 2003
PDF: 11 pages
Proc. SPIE 5098, Data Mining and Knowledge Discovery: Theory, Tools, and Technology V, (21 March 2003); doi: 10.1117/12.486997
Show Author Affiliations
John J. Salerno, Air Force Research Lab. (United States)
Doug M. Boulware, Air Force Research Lab. (United States)
John E. Myers, Air Force Research Lab. (United States)
Vishal Khattri, Air Force Research Lab. (United States)
Dave R. Corzillus, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 5098:
Data Mining and Knowledge Discovery: Theory, Tools, and Technology V
Belur V. Dasarathy, Editor(s)

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