This paper describes the FACT system for knowledge discovery from text. It discovers associations - patterns of co-occurrence -amongst keywords labeling the items in a collection of textual documents. In addition, FACT is able to use background knowledge about the keywords labeling the documents in its discovery process. FACT takes a query-centered view of knowledge discovery, in which a discovery request is viewed as a query over the implicit set of possible results supported by a collection of documents, and where background knowledge is used to specify constraints on the desired results of this query process. Execution of a knowledge-discovery query is structured so that these background-knowledge constraints can be exploited in the search for possible results. Finally, rather than requiring a user to specify an explicit query expression in the knowledge-discovery query language, FACT presents the user with a simple-to-use graphical interface to the query language, with the language providing a well-defined semantics for the discovery actions performed by a user through the interface.
|Original language||American English|
|Title of host publication||Proceedings - 2nd International Conference on Knowledge Discovery and Data Mining, KDD 1996|
|Editors||Evangelos Simoudis, Jiawei Han, Usama M. Fayyad|
|Number of pages||4|
|ISBN (Electronic)||1577350049, 9781577350040|
|State||Published - 1996|
|Event||2nd International Conference on Knowledge Discovery and Data Mining, KDD 1996 - Portland, United States|
Duration: 2 Aug 1996 → 4 Aug 1996
|Name||Proceedings - 2nd International Conference on Knowledge Discovery and Data Mining, KDD 1996|
|Conference||2nd International Conference on Knowledge Discovery and Data Mining, KDD 1996|
|Period||2/08/96 → 4/08/96|
Bibliographical notePublisher Copyright:
© 1996 AAAI (www.aaai.org). All Rights Reserved.