文章基本信息

标题：Comparative Study of Truncating and Statistical Stemming Algorithms
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作者：Sanaullah Memon ; Ghulam Ali Mallah ; K.N.Memon 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2020
卷号：11
期号：2
DOI：10.14569/IJACSA.2020.0110272
出版社：Science and Information Society (SAI)
摘要：Search and indexing systems bear a significant quality called word stemming, is lump of content excavating requests, IR frameworks and natural language handling frameworks. The fundamental topic in the search and indexing through time is to upgrade infer via robotized diminishing and fussing of the words into word roots. From index term by evacuating any connected prefixes and postfixes, Stemming is done to proceeding piece of work of index word, and more extensive idea than the real word is spoken by trunk. In an IR framework, the numeral of recovered archives is expanded by stemming process.
关键词：Stemming; truncating; statistical; NLP; IR; Lovins; Porters; Paice/Husk; Dawson; N-gram; HMM; YASS