Mining the Web for Knowledge with Sub-Optimal Mining Algorithm

  • Authors:
  • Stuart H. Rubin;Marion G. Ceruti;Lydia C. Shen

  • Affiliations:
  • -;-;-

  • Venue:
  • COMPSAC '00 24th International Computer Software and Applications Conference
  • Year:
  • 2000

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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.