Premium
Question Classification for Chinese Cuisine Question Answering System
Author(s) -
Xia Ling,
Teng Zhi,
Ren Fuji
Publication year - 2009
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.20466
Subject(s) - preprocessor , question answering , classifier (uml) , support vector machine , exploit , computer science , artificial intelligence , domain (mathematical analysis) , natural language processing , the internet , machine learning , data mining , world wide web , mathematics , mathematical analysis , computer security
This paper presents an integrated method on question classification for Chinese cuisine question answering (QA) system. First, we exploit the domain knowledge to enrich question preprocessing, then classification features are extracted by means of domain attributes and the rule‐based classifier is constructed. Support vector machine (SVM) classifier is used for secondary classification to the questions which cannot be matched with rules. A prototype system based on the proposed method has been constructed and an experiment on 453 natural language questions collected from Internet has been carried out. It achieved an accuracy of 96.22%. Result shows that a small number of linguistically motivated domain features can efficiently classify questions of Chinese cuisine QA system. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.