A statistical classification approach to question answering using Web data

Author

Whittaker, Edward ; Furui, Sadaoki ; Klakow, Dietrich

Author_Institution

Dept. of Comput. Sci., Tokyo Inst. of Technol.

fYear

2005

fDate

23-25 Nov. 2005

Lastpage

428

Abstract

In this paper we treat question answering (QA) as a classification problem. Our motivation is to build systems for many languages without the need for highly tuned linguistic modules. Consequently, word tokens and Web data are used extensively but no explicit linguistic knowledge is incorporated. A mathematical model for answer retrieval, answer classification and answer length prediction is derived. The TREC 2002 QA task is used for system development where 33% of questions are answered correctly. Performance is then evaluated on the factoid questions of the TREC 2003 QA task where 23% of questions were answered correctly, which would rank the system in the top 10 of contemporary QA systems on the same task

Keywords

Internet; classification; information retrieval; natural languages; statistical analysis; QA systems; TREC; Web data; answer classification; answer length prediction; answer retrieval; classification problem; factoid questions; question answering; statistical classification; Computer science; Data mining; Information analysis; Mathematical model; Robustness; Search engines; Statistical analysis; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Cyberworlds, 2005. International Conference on

Conference_Location

Singapore

Print_ISBN

0-7695-2378-1

Type

conf

DOI

10.1109/CW.2005.10

Filename

1587573