scholarly journals STEMMING BAHASA JAWA MENGGUNAKAN DAMERAU LEVENSHTEIN DISTANCE (DLD)

2021 ◽  
Vol 14 (1) ◽  
pp. 22-27
Author(s):  
Aji Prasetya Wibawa ◽  
Muhammad Nu’man Hakim
Keyword(s):  
Text Mining ◽  
Test Data ◽  
String Matching ◽  
Levenshtein Distance ◽  
Matching Algorithm ◽  
Word Repetition ◽  
Basic Word ◽  
Word Forms

Stemming is one of the essential stages of text mining. This process removes prefixes and suffixes to produce root words in a text. This study uses a string matching algorithm, namely Damerau Levenshtein Distance (DLD), to find the basic word forms of Javanese. Test data of 300 words that have a prefix, insertion, suffix, a combination of prefix and suffix, and word repetition. The results of this study indicate that the Damerau Levenshtein Distance (DLD) algorithm can be used for Stemming Javanese text with an accuracy value of 49.6%.

scholarly journals Contribution to Semantic Analysis of Arabic Language

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Anis Zouaghi ◽  
Mounir Zrigui ◽  
Georges Antoniadis ◽  
Laroussi Merhbene
Keyword(s):  
Information Retrieval ◽  
Semantic Analysis ◽  
String Matching ◽  
Ambiguous Word ◽  
Arabic Language ◽  
New Approach ◽  
Matching Algorithm ◽  
Ambiguous Words ◽  
Lesk Algorithm ◽  
Context Of Use

We propose a new approach for determining the adequate sense of Arabic words. For that, we propose an algorithm based on information retrieval measures to identify the context of use that is the closest to the sentence containing the word to be disambiguated. The contexts of use represent a set of sentences that indicates a particular sense of the ambiguous word. These contexts are generated using the words that define the senses of the ambiguous words, the exact string-matching algorithm, and the corpus. We use the measures employed in the domain of information retrieval, Harman, Croft, and Okapi combined to the Lesk algorithm, to assign the correct sense of those proposed.

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