Name
Abstract | ||
|---|---|---|
This paper describes the FACT system for knowledge discovery fromtext. It discovers associations—patterns ofco-occurrence—amongst keywords labeling the items in a collection oftextual documents. In addition, when background knowledge is available aboutthe keywords labeling the documents FACT is able to use this information inits discovery process. FACT takes a query-centered view of knowledgediscovery, in which a discovery request is viewed as a query over theimplicit set of possible results supported by a collection of documents, andwhere background knowledge is used to specify constraints on the desiredresults of this query process. Execution of a knowledge-discovery query isstructured so that these background-knowledge constraints can be exploitedin the search for possible results. Finally, rather than requiring a user tospecify an explicit query expression in the knowledge-discovery querylanguage, FACT presents the user with a simple-to-use graphical interface tothe query language, with the language providing a well-defined semantics forthe discovery actions performed by a user through the interface. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1023/A:1008693204338 | J. Intell. Inf. Syst. |
Keywords | Field | DocType |
association mining,textual databases,background knowledge,query languages,constraint processing | Query optimization,Data mining,Web search query,Query language,RDF query language,Information retrieval,Query expansion,Computer science,Sargable,Web query classification,Ranking (information retrieval) | Journal |
Volume | Issue | ISSN |
9 | 1 | 1573-7675 |
Citations | PageRank | References |
20 | 3.86 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ronen Feldman | 1 | 1336 | 146.23 |
| Haym Hirsh | 2 | 1839 | 277.74 |