QUESTION ANSWERING USING QUESTION CLASSIFICATION AND DOCUMENT TAGGING

被引：3

作者：

Chali, Yllias ^{[1
]}

机构：

[1] Univ Lethbridge, Dept Comp Sci, Lethbridge, AB T1K 3M4, Canada

来源：

APPLIED ARTIFICIAL INTELLIGENCE | 2009年 / 23卷 / 06期

关键词：

Document tagging - Question Answering - Question answering systems - Question classification - Text retrieval conferences;

D O I：

10.1080/08839510903078093

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Question answering (QA) is a relatively new area of research. We took the approach of designing a question answering system that is based on question classification and document tagging. Question classification extracts useful information from the question about how to answer the question. Document tagging extracts useful information from the documents, which are used to find the answer to the question. We used different available systems to tag the documents. Our system classifies the questions using manually developed rules. An evaluation of the system is performed using Text REtrieval Conference (TREC) data.

引用

页码：500 / 521

页数：22

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