Mining the Web for knowledge with sub-optimal mining algorithms

Author

Rubin, Stuart H. ; Ceruti, Marion G. ; Shen, Lydia C.

Author_Institution

Space & Naval Warfare Syst. Center, San Diego, CA, USA

fYear

2000

fDate

2000

Firstpage

184

Lastpage

186

Abstract

The Web provides a forum in which AI systems can be demonstrated and compared. This paper addresses a fuzzy method for context-sensitive textual matching. We are investigating two key approaches. Knowledge on the Web must be retrieved and structured to facilitate mining operations. Case-based filtering allows the algorithm to adapt dynamically to changes in content or efficiency of expression. Our approach is to design sub-optimal mining algorithms that sacrifice completeness for speed, tractability and breadth of coverage. The mined knowledge is fed back to serve as a heuristic filter

Keywords

Internet; data mining; information resources; pattern matching; relevance feedback; text analysis; AI systems; Web; beam-search; case-based filtering; context-sensitive textual matching; fuzzy method; heuristic filter; semantic-relevance ranking system; sub-optimal mining algorithms; Algorithm design and analysis; Artificial intelligence; Data mining; Filtering algorithms; Filters; Heuristic algorithms; Internet; Table lookup; USA Councils; Web pages;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Software and Applications Conference, 2000. COMPSAC 2000. The 24th Annual International

Conference_Location

Taipei

ISSN

0730-3157

Print_ISBN

0-7695-0792-1

Type

conf

DOI

10.1109/CMPSAC.2000.884714

Filename

884714