Performance Evaluation of Knowledge Extraction Methods

被引：7

作者：

Rodriguez, Juan M. ^{[1
,2
,3
]}

Merlino, Hernan D. ^{[2
,3
]}

Pesado, Patricia ^{[4
]}

Garcia-Martinez, Ramon ^{[3
]}

机构：

[1] Natl Univ La Plata, PhD Program Comp Sci, La Plata, Buenos Aires, Argentina

[2] Univ Buenos Aires, Intelligent Syst Grp, Buenos Aires, DF, Argentina

[3] Natl Univ Lanus, Informat Syst Res Grp, Lanus, Argentina

[4] Natl Univ La Plata, Sch Comp Sci, III LIDI, CIC Bs As, La Plata, Buenos Aires, Argentina

来源：

TRENDS IN APPLIED KNOWLEDGE-BASED SYSTEMS AND DATA SCIENCE | 2016年 / 9799卷

关键词：

D O I：

10.1007/978-3-319-42007-3_2

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 shows the precision, the recall and the F-measure for the knowledge extraction methods (under Open Information Extraction paradigm): ReVerb, OLLIE and ClausIE. For obtaining these three measures a subset of 55 newswires corpus was used. This subset was taken from the Reuters-21578 text categorization and test collection database. A handmade relation extraction was applied for each one of these newswires.

引用

页码：16 / 22

页数：7

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