A Classification Model with Corpus Enrichment for Toponym Disambiguation

被引：0

作者：

Priego Sanchez, Belem ^{[1
]}

Somodevilla, Maria J. ^{[1
]}

Guzman Cabrera, Rafael ^{[2
]}

Pineda, Ivo H. ^{[1
]}

Carrillo, Maya ^{[1
]}

机构：

[1] Benemerita Univ Autonoma Puebla, FCC, Av San Claudio & 14 S, Puebla, Mexico

[2] Univ Guanajuato, DICIS, Salamanca, Mexico

来源：

ADVANCES IN ARTIFICIAL INTELLIGENCE - IBERAMIA 2012 | 2012年 / 7637卷

关键词：

toponym disambiguation; geographic information retrieval; corpus; classification model; WORD SENSE DISAMBIGUATION; WEB;

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 method based on information retrieval to enrich corpus using bootstrapping techniques. A supervised corpus manually validated is provided, and then snippets are obtained from Web in order to increase the size of the initial corpus. Although this technique has already been reported in the literature, the main objective of this work is to apply it under the specific task of GEO/NO-GEO toponym disambiguation. The disambiguation procedure is evaluated by a classification model observing favorable results.

引用

页码：472 / 480

页数：9

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