Combination of Rough Set Theory and Maximum Entropy Model for Conjunctive Structure Detection in QA System

Author

Fan, Shi-Xi ; Wang, Xuan ; Wang, Xiao-long

Author_Institution

Harbin Inst. of Technol., Shenzhen

Volume

6

fYear

2007

fDate

19-22 Aug. 2007

Firstpage

3051

Lastpage

3056

Abstract

We introduce a combination model as conjunctive structures detection for question pre-processing in Q&A system. Conjunctive structures detection can be treated as a pattern recognition problem. The rough set theory is used for selecting effective features and the ME (maximum entropy) model is used for building a pattern classifier to get high accuracy. The training and testing data are collected from some discussion groups in the internet. A simple ME model is used for baseline system. The best Precision is 0.932 with 0.042 higher than the baseline system.

Keywords

Internet; maximum entropy methods; rough set theory; Internet; combination model; conjunctive structure detection; maximum entropy model; pattern classifier; pattern recognition problem; question and answer system; question preprocessing; rough set theory; Buildings; Computer science; Cybernetics; Electronic mail; Entropy; Internet; Machine learning; Pattern recognition; Search engines; Set theory; Conjunctive structure; Maximum entropy; QA; Rough set theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2007 International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-0973-0

Electronic_ISBN

978-1-4244-0973-0

Type

conf

DOI

10.1109/ICMLC.2007.4370672

Filename

4370672