Title :
Data mining on text
Author :
Clifton, Chris ; Steinheiser, Rick
Author_Institution :
Mitre Corp., Bedford, MA, USA
Abstract :
Data mining technology is giving us the ability to extract meaningful patterns from large quantities of structured data. Information retrieval systems have made large quantities of textual data available. Extracting meaningful patterns from this data is difficult. Current tools for mining structured data are inappropriate for free text. We outline problems involved in Knowledge Discovery in Text, and present an architecture for extracting patterns that hold across multiple documents. The capabilities that such a system could provide are illustrated
Keywords :
information retrieval; knowledge acquisition; very large databases; Knowledge Discovery in Text; data mining; multiple documents; structured data; textual data; Data engineering; Data mining; Database languages; Engines; Filters; Information retrieval; Marketing and sales; Mining industry; Text mining; US Department of Defense;
Conference_Titel :
Computer Software and Applications Conference, 1998. COMPSAC '98. Proceedings. The Twenty-Second Annual International
Conference_Location :
Vienna
Print_ISBN :
0-8186-8585-9
DOI :
10.1109/CMPSAC.1998.716738