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An Empirical Research on Extracting Relations from Wikipedia Text

TitleAn Empirical Research on Extracting Relations from Wikipedia Text
Publication TypeBook Chapter
Year of Publication2008
AuthorsHuang, J-X, Ryu, P-M, Choi, K-S
EditorFyfe, C, Kim, D, Lee, S-Y, Yin, H
Book TitleIntelligent Data Engineering and Automated Learning – IDEAL 2008
Series TitleLecture Notes in Computer Science
Volume5326
Pagination241-249
PublisherSpringer
CityBerlin / Heidelberg
ISBN978-3-540-88905-2
Abstract

A feature based relation classification approach is presented, in which probabilistic and semantic relatedness features between patterns and relation types are employed with other linguistic information. The importance of each feature set is evaluated with Chi-square estimator, and the experiments show that, the relatedness features have big impact on the relation classification performance. A series experiments are also performed to evaluate the different machine learning approaches on relation classification, among which Bayesian outperformed other approaches including Support Vector Machine (SVM).

URLhttp://csace.kaist.ac.kr/~pmryu/pub/2008IDEAL.pdf
DOI10.1007/978-3-540-88906-9_31