Mining Wikipedia Resources for Discovering Answers to List Questions in Web Snippets

Author

Figueroa, Alejandro

Author_Institution

German Centre for Artificial Intell. - DFKI, Saarbrucken, Germany

fYear

2008

fDate

3-5 Dec. 2008

Firstpage

133

Lastpage

140

Abstract

This paper presents LiSnQA, a list question answering system that extracts answers to list queries from the short descriptions of Web-sites returned by search engines, called Web snippets. LiSnQA mines Wikipedia resources in order to obtain valuable information that assists in the extraction of these answers. The interesting facet of LiSnQA is, that in contrast to current systems, it does not account for lists in Wikipedia, but for its redirections, categories, sandboxes, and first definition sentences. Results show that these resources strengthen the answering process.

Keywords

Web sites; data mining; information retrieval; LiSnQA; Web sites; Web snippets; Wikipedia resources mining; list question answering system; Artificial intelligence; Books; Data mining; Encyclopedias; Internet; Natural languages; Pattern recognition; Search engines; Wikipedia; List Questions; Mining Wikipedia; Question Answering on the web; Question Anwering; Web Mining; Web Question Answering; Web Snippets; Wikipedia;

fLanguage

English

Publisher

ieee

Conference_Titel

Semantics, Knowledge and Grid, 2008. SKG '08. Fourth International Conference on

Conference_Location

Beijing

Print_ISBN

978-0-7695-3401-5

Electronic_ISBN

978-0-7695-3401-5

Type

conf

DOI

10.1109/SKG.2008.31

Filename

4725906