Comparative Study of Truncating and Statistical Stemming Algorithms

被引：0

作者：

Memon, Sanaullah ^{[1
]}

Mallah, Ghulam Ali ^{[2
]}

Memon, K. N. ^{[3
]}

Shaikh, A. G. ^{[4
]}

Aasoori, Sunny K. ^{[4
]}

Dehraj, Faheem Ul Hussain ^{[5
]}

机构：

[1] Shaheed Benazir Bhutto Univ, Dept Informat Technol, Shaheed Benazirabad Sind, Pakistan

[2] SALU, Dept Comp Sci, Khairpur, Sindh, Pakistan

[3] QUEST, Dept Math & Stat, Nawabshah, Sindh, Pakistan

[4] QUEST, Dept BSRS, Nawabshah, Sindh, Pakistan

[5] Shaheed Benazir Bhutto Univ, Dept Business Adm, Shaheed Benazirabad, Sindh, Pakistan

来源：

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS | 2020年 / 11卷 / 02期

关键词：

Stemming; truncating; statistical; NLP; IR; Lovins; Porters; Paice/Husk; Dawson; N-gram; HMM; YASS;

D O I：

10.14569/ijacsa.2020.0110272

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

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.

引用

页码：563 / 568

页数：6

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