Name
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. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/CMPSAC.2000.884714 | COMPSAC |
Keywords | Field | DocType |
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 | Data mining,Data stream mining,Relevance feedback,Computer science,The Internet,World Wide Web,Concept mining,Heuristic,Information retrieval,Algorithm,Filter (signal processing),Pattern matching,Completeness (statistics) | Conference |
Volume | ISSN | ISBN |
24 | 0730-3157 | 0-7695-0792-1 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stuart Harvey Rubin | 1 | 73 | 20.96 |
| Marion G. Ceruti | 2 | 126 | 27.87 |
| Lydia C. Shen | 3 | 0 | 0.34 |