Mining associations in text in the presence of background knowledge

Conference · Tue Dec 31 04:00:00 EST 1996

OSTI ID:421309

Feldman, R ^[1]; Hirsh, H ^[2]

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1. Bar-Ilan Univ., Ramat-Gan (Israel)
2. Rutgers Univ., Piscataway, NJ (United States)

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 back-ground-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.

• OSTI ID: 421309
• Report Number(s): CONF-960830--
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
ALGORITHMS
ARTIFICIAL INTELLIGENCE
DATA BASE MANAGEMENT
INFORMATION RETRIEVAL
KNOWLEDGE BASE
PROGRAMMING LANGUAGES