Title :
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
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;
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
DOI :
10.1109/ICMLC.2007.4370672
