Back to Search Start Over

Multi-words Terminology Recognition Using Web Search

Authors :
Sung-Pil Choi
Yun-Soo Choi
Won-Kyung Sung
Sa-Kwang Song
Chang-Hoo Jeong
Hong-Woo Chun
Source :
U-and E-Service, Science and Technology ISBN: 9783642272097, FGIT-UNESST
Publication Year :
2011
Publisher :
Springer Berlin Heidelberg, 2011.

Abstract

Terminology recognition system which is a fundamental research for Technology Opportunity Discovery (TOD) has been intensively studied in limited range of domains, especially in bio-medical domain. We propose a domain independent terminology recognition system based on machine learning method using dictionary, syntactic features, and Web search results, since the previous works revealed limitation on applying their approaches to general domain because their resources were domain specific. We achieved F-score 80.4 and 6.4% improvement after comparing the proposed approach with the related approach, C-value, which has been widely used and is based on local domain frequencies. In the second experiment with various combinations of unithood features, the method combined with NGD(Normalized Google Distance) showed the best performance of 81.5 on F-score. We applied two machine learning methods such as Logistic regression and SVMs, and got the best score at SVMs method.

Details

ISBN :
978-3-642-27209-7
ISBNs :
9783642272097
Database :
OpenAIRE
Journal :
U-and E-Service, Science and Technology ISBN: 9783642272097, FGIT-UNESST
Accession number :
edsair.doi...........fb1657e980a84c6ce5c4356ea5ca5958
Full Text :
https://doi.org/10.1007/978-3-642-27210-3_29