DocumentCode :
2697719
Title :
Extraction of keyterms by simple text mining for business information retrieval
Author :
Gao, Xiangzhu ; Murugesan, San ; Lo, Bruce
Author_Institution :
Southern Cross Univ., Lismore, NSW
fYear :
2005
fDate :
12-18 Oct. 2005
Firstpage :
332
Lastpage :
339
Abstract :
Much of business information is text and the information is subject to frequent changes. The use of efficient and effective mechanisms to retrieve required business information is a key to business success, and automated processing of text to extract key terms is an essential component of such an information retrieval (IR) system. Traditional text processing methods based on complex linguistic or statistic techniques are not efficient in dealing with frequently changing business information and do not necessarily provide satisfying IR results. We propose a simple method to extract important terms (keyterms) from text for application in different aspects of IR and show through experimentation that its performance is comparable to or better than complex methods
Keywords :
business data processing; data mining; indexing; information retrieval; text analysis; business information retrieval; keyterms extraction; linguistic technique; statistic technique; text mining; text processing; Data mining; Humans; Indexing; Information retrieval; Search engines; Text mining; Text processing; Thesauri; Vocabulary; Web pages;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
e-Business Engineering, 2005. ICEBE 2005. IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2430-3
Type :
conf
DOI :
10.1109/ICEBE.2005.66
Filename :
1552912
Link To Document :
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