Mutual screening graph algorithm: A new bootstrapping algorithm for lexical acquisition

Abstract

Bootstrapping is a weakly supervised algorithm that has been the focus of attention in many Information Extraction(IE) and Natural Language Processing(NLP) fields, especially in learning semantic lexicons. In this paper, we propose a new bootstrapping algorithm called Mutual Screening Graph Algorithm (MSGA) to learn semantic lexicons. The approach uses only unannotated corpus and a few of seed words to learn new words for each semantic category. By changing the format of extracted patterns and the method for scoring patterns and words, we improve the former bootstrapping algorithm. We also evaluate the semantic lexicons produced by MSGA with previous bootstrapping algorithm Basilisk [1] and GMR (Graph Mutual Reinforcement based Bootstrapping) [4]. Experiments have shown that MSGA can outperform those approaches. © 2009 Springer Berlin Heidelberg.