Using Genetic Algorithm for Persian Grammar Induction

摘要：

Most of efficient computational approaches in NLP tasks are supervised methods which need annotated corpora. But the lack of supervised data in Persian encourages researchers to increase their interests and efforts on unsupervised and semi-supervised approaches. This paper presents a novel semi-supervised approach which called Genetic-based insideoutside (GIO), for Persian grammar inference for inducing a grammar model in a PCFG formalism. GIO is an extension of the insideoutside algorithm enriched by some notions of genetic algorithm. In pure genetic algorithm for grammar induction, randomly generated initial population make it computationally expensive, so we used inside-outside algorithm to generate initial population. Our experiments show that our approach’s result is better than other applied methods for Persian grammar induction.

关键词： Grammar induction genetic algorithm inside-outside algorithm Persian grammar

作者: Mohsen Arabsorkhi Hesham Faili Mansoor Zolghadri Jahroumi

作者单位: Computer Engineering Dept., Islamic Azad University of Saveh Saveh, Iran Computer Engineering Dept., Tehran University Tehran, Iran Computer Science and Engineering Dept., Shiraz University Shiraz, Iran

会议类型: 国际会议

会议名称: International Conference on Natural Language Processing and Knowledge Engineering(IEEE自然语言处理与知识工程国际会议 IEEE NLP-KE 2009)

会议地点: 大连

会议语种:英文

页码: 1-6

在线出版日期: 2009-09-24（万方平台首次上网日期，不代表论文的发表时间）