Unsupervised incremental acquisition of a thematic corpus from the Web

被引：0
|
作者：
Duclaye, F [1 ]
Yvon, F [1 ]
Collin, O [1 ]
机构：
[1] France Telecom, R&D, F-22307 Lannion, France
来源：
2003 INTERNATIONAL CONFERENCE ON NATURAL LANGUAGE PROCESSING AND KNOWLEDGE ENGINEERING, PROCEEDINGS | 2003年
关键词：
paraphrases; synonyms; machine learning; Web; automatic classification; EM;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a nearly unsupervised learning methodology for automatically acquiring a thematic corpus from the Web. Relying on a bootstrapping mechanism, our system starts with one single linguistic expression of a given target, semantic relationship. It then samples the Web so as to progressively accumulate a corpus of potential examples of the same relationship. Sampling steps alternate with filtering steps, making it possible to keep the corpus thematically focused. The corpus is finally analysed to search for potential paraphrases of the initial expression of the semantic relationship. These paraphrases will eventually be used to improve our question-answering system. This paper focuses on the learning aspect of the system and reports experimental results regarding the effectiveness of our filtering strategy.
引用
收藏
页码：752 / 757
页数：6
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