Bootstrapping a Semantic Lexicon on Verb Similarities

被引：4

作者：

Syed, Shaheen ^{[1
]}

Spruit, Marco ^{[1
]}

Borit, Melania ^{[2
]}

机构：

[1] Univ Utrecht, Dept Informat & Comp Sci, Utrecht, Netherlands

[2] Univ Tromso, Norwegian Coll Fishery Sci, Tromso, Norway

来源：

KDIR: PROCEEDINGS OF THE 8TH INTERNATIONAL JOINT CONFERENCE ON KNOWLEDGE DISCOVERY, KNOWLEDGE ENGINEERING AND KNOWLEDGE MANAGEMENT - VOL. 1 | 2016年

关键词：

Semantic Lexicon; Bootstrapping; Extraction Patterns; Web Mining;

D O I：

10.5220/0006036901890196

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a bootstrapping algorithm to create a semantic lexicon from a list of seed words and a corpus that was mined from the web. We exploit extraction patterns to bootstrap the lexicon and use collocation statistics to dynamically score new lexicon entries. Extraction patterns are subsequently scored by calculating the conditional probability in relation to a non-related text corpus. We find that verbs that are highly domain related achieved the highest accuracy and collocation statistics affect the accuracy positively and negatively during the bootstrapping runs.

引用

页码：189 / 196

页数：8

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