Exploiting Background Information in Knowledge Discovery from Text

被引：10

作者：

Feldman R. ^{[1
]}

Hirsh H. ^{[2
]}

机构：

[1] Math. and Comp. Science Department, Bar-Ilan University, Ramat-Gan

[2] Department of Computer Science, Rutgers University, Piscataway

来源：

Journal of Intelligent Information Systems | 1997年 / 9卷 / 1期

基金：

美国国家科学基金会;

关键词：

Association mining; Background knowledge; Constraint processing; Query languages; Textual databases;

D O I：

10.1023/A:1008693204338

中图分类号：

学科分类号：

摘要：

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.

引用

页码：83 / 97

页数：14

共 11 条

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