Applying question classification to Yahoo! Answers

Mohan John Blooma, Dion Hoe Lian Goh, Alton Yeow Kuan Chua, Zhiquan Ling

Research output: A Conference proceeding or a Chapter in BookConference contribution

4 Citations (Scopus)

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.

Original languageEnglish
Title of host publication1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages229-234
Number of pages6
ISBN (Print)9781424426249
DOIs
Publication statusPublished - 30 Dec 2008
Externally publishedYes
Event1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008 - Ostrava, Czech Republic
Duration: 4 Aug 20086 Aug 2008

Publication series

Name1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008

Conference

Conference1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008
CountryCzech Republic
CityOstrava
Period4/08/086/08/08

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