Exploiting Background Information in Knowledge Discovery from Text

Abstract

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, when background knowledge is available about the keywords labeling the documents FACT is able to use this information 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.