Applying question classification to Yahoo! Answers

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 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
Pages229-234
Number of pages6
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008 - Ostrava, Czech Republic
Duration: Aug 4 2008Aug 6 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
Country/TerritoryCzech Republic
CityOstrava
Period8/4/088/6/08

ASJC Scopus Subject Areas

  • Computer Science Applications
  • Information Systems
  • Software

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