Implemented Stemming Algorithms for Information Retrieval Applications

Wubetu Barud Demilie
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引用次数: 1

Abstract

Now a day’s text documents are advancing over internet, e-mails and web pages. As the use of internet is exponentially growing, the need of massive data storage is increasing from time to time.  Normally many of the documents contain morphological variables, so stemming which is a preprocessing technique gives a mapping of different morphological variants of words into their base word called the stem. Stemming process is used in information retrieval applications accordingly as a way to improve retrieval performance based on the assumption that terms with the same stem usually have similar meaning.  To do stemming operation on bulky documents, we require normally more computation time and power, to cope up with the need to search for a particular word in the data. In this paper, various stemming algorithms are analyzed with the benefits and limitation of the recent stemming methods or approaches. Keywords : - Natural Language Processing Applications, Information Retrieval, Information Retrieval Applications (IRAs), Stemming Approaches DOI: 10.7176/JIEA/10-3-01 Publication date: April 30 th 2020
为信息检索应用实现的词干提取算法
如今,每天的文本文件都在通过互联网、电子邮件和网页推进。随着互联网的使用呈指数级增长,对海量数据存储的需求也在不断增加。通常,许多文档都包含词法变量,因此词干提取是一种预处理技术,它将单词的不同词法变体映射到它们的基词中,称为词干。基于相同词干的术语通常具有相似的含义这一假设,词干提取过程作为一种提高检索性能的方法被应用于信息检索应用中。为了对庞大的文档进行词干提取操作,我们通常需要更多的计算时间和功率,以应付在数据中搜索特定单词的需要。本文对各种词干提取算法进行了分析,分析了现有词干提取方法的优缺点。关键词:自然语言处理应用,信息检索,信息检索应用,词干提取方法DOI: 10.7176/JIEA/10-3-01出版日期:2020年4月30日
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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