Autonomy Stemmer Algorithm for Legal and Illegal Affix Detection use Finite-State Automata Method

Ana Tsalisatun Ni'mah, D. Suryaningrum, A. Arifin
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引用次数: 2

Abstract

Stemming is the process of separating words from their affixes to get a basic word. Stemming is generally used when preprocessing in text-based applications. Indonesian Stemming has developed research which is divided into two types, namely, stemming without dictionaries and stemming using dictionaries. Stemming without dictionaries has a disadvantage in the results of removal of affixes which are sometimes inappropriate so that it results in over stemming or under stemming, while stemming using dictionaries has a disadvantage during the stemming process which is relatively long and cannot eliminate affixes to compound words. This study proposes a new stemming algorithm without a dictionary that is able to detect legal and illegal affixes in Indonesian using the Finite-State Automata method. The technique used is rule-based Stemmer based on Indonesian language morphology with Regular Expression. Test results were carried out using 118 news documents with 15792 words. The first test results on the autonomy stemmer algorithm obtain the correct word which amounts to 10449 of the total number of words processed, which means getting an average accuracy of 66%. The second test results on the autonomy stemmer algorithm get the results of the average speed of 0.0051 seconds. The third test result is being able to do the elimination of affixes to compound words.
使用有限状态自动机方法进行合法和非法词缀检测的自主词干算法
词干是将单词从词缀中分离出来,得到一个基本单词的过程。词干提取通常用于基于文本的应用程序的预处理。印尼语词干研究的发展分为无词典词干和有词典词干两种类型。无词典词干法的缺点是词缀有时不合适,会导致词缀过度词干或词缀不足,而词典词干法的缺点是词干过程较长,不能消除复合词的词缀。本研究提出了一种新的词干提取算法,该算法使用有限状态自动机方法可以在没有字典的情况下检测印尼语的合法和非法词缀。使用的技术是基于规则的词法,该词法基于印尼语的正则表达式。测试结果采用118篇新闻文献,15792个单词。自主词干算法的第一次测试结果得到了正确的单词,达到了处理单词总数的10449个,平均准确率达到66%。对自主干模算法的第二次测试结果得到平均速度为0.0051秒的结果。第三个测试结果是能够消除复合词的词缀。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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