DocumentCode
3255865
Title
Applying question classification to Yahoo! Answers
Author
Blooma, Mohan John ; Goh, Dion Hoe-Lian ; Chua, Alton Yeow Kuan ; Ling, Zhiquan
Author_Institution
Wee Kim Wee Sch. of Commun. & Inf., Nanyang Technol. Univ., Singapore
fYear
2008
fDate
4-6 Aug. 2008
Firstpage
229
Lastpage
234
Abstract
Question classification is an important part in modern Question Answering systems. Most approaches to question classification are based on handcrafted rules. Recent studies classify simple questions using machine learning techniques and recommends SVM as on of the best performing classifiers. This study applies a hierarchical classifier based on the SVM machine learning algorithm on questions posed by users, drawn from Yahoo! Answers. The significance of this study is that we attempted to directly classify complex questions with multiple sentence questions posed by real users. We report the accuracy achieved using both a coarse-grained classifier and fine-grained classifier to illustrate the effectiveness of our approach on complex questions. We also present a confusion matrix to analyze the results made by our classifier.
Keywords
Internet; information retrieval; learning (artificial intelligence); natural language processing; pattern classification; support vector machines; Question Answering systems; Yahoo! Answers; hierarchical classifier; machine learning; question classification; support vector machine; Books; Internet; Machine learning; Machine learning algorithms; Natural language processing; Natural languages; Software libraries; Support vector machine classification; Support vector machines; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Applications of Digital Information and Web Technologies, 2008. ICADIWT 2008. First International Conference on the
Conference_Location
Ostrava
Print_ISBN
978-1-4244-2623-2
Electronic_ISBN
978-1-4244-2624-9
Type
conf
DOI
10.1109/ICADIWT.2008.4664350
Filename
4664350
Link To Document