Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom

Latent Semantic Analysis (LSA) algorithm is a mathematical approach that uses Singular Value Decomposition (SVD) to discover the important association of the relationship between terms and terms, terms and documents and also documents and documents. Furthermore, LSA uses cosine similarity measuremen...

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Main Author:	Md Soom, Afiqah Bazlla
Format:	Thesis
Language:	English
Published:	2018
Subjects:	Analysis Algorithms
Online Access:	https://ir.uitm.edu.my/id/eprint/26905/1/TM_AFIQAH%20BAZLLA%20MD%20SOOM%20CS%2018_5.pdf
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id	my-uitm-ir.26905
record_format	uketd_dc
spelling	my-uitm-ir.269052022-11-14T06:13:46Z Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom 2018 Md Soom, Afiqah Bazlla Analysis Algorithms Latent Semantic Analysis (LSA) algorithm is a mathematical approach that uses Singular Value Decomposition (SVD) to discover the important association of the relationship between terms and terms, terms and documents and also documents and documents. Furthermore, LSA uses cosine similarity measurement to measure the similarity between the query word and terms as well as the documents. This approach seem to be efficient if each of the term only have single meaning and a meaning only represent a single term. Unfortunately, in Malay language there exists many terms that have multiple meanings and a single meaning that are represented by multiple terms. If these terms are treated as a single word, it will lead the search engine to retrieve irrelevant documents. These irrelevant documents retrieved will effect the effectiveness of the search engine. To investigate the enhancement of LSA using tagging algorithm (LSAT) in retrieving Malay documents, eight experiments are conducted in this research. The first experiment is conducted to compare the time taken for extracting normal term list and tagged term list, total number of both lists and also the time taken for the creation of term document matrix. Another six experiments record all the results of the LSA and LSAT search engine by using different dimension and threshold value. While the last experiment to compare the LSAT result with previous work on LSA using the same test collection. Outcomes of this study indicate that by using tagging algorithm, the recall value of the LSA algorithm can be enhanced up to 4% , the precision value also can be enhanced up to 16% and the F-measure value of LSA retrieval result can be enhanced by approximately up to 7% compared to LSA retrieval result without tagging algorithm. Furthermore, this research provides fundamental analyses to the other Information Retrieval (IR) developer in selecting the value of dimension and threshold value of retrieval that using LSA. 2018 Thesis https://ir.uitm.edu.my/id/eprint/26905/ https://ir.uitm.edu.my/id/eprint/26905/1/TM_AFIQAH%20BAZLLA%20MD%20SOOM%20CS%2018_5.pdf text en public masters Universiti Teknologi MARA Faculty of Computer Science and Mathematics Abd. Rahman, Nurazzah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Abd. Rahman, Nurazzah
topic	Analysis Algorithms
spellingShingle	Analysis Algorithms Md Soom, Afiqah Bazlla Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom
description	Latent Semantic Analysis (LSA) algorithm is a mathematical approach that uses Singular Value Decomposition (SVD) to discover the important association of the relationship between terms and terms, terms and documents and also documents and documents. Furthermore, LSA uses cosine similarity measurement to measure the similarity between the query word and terms as well as the documents. This approach seem to be efficient if each of the term only have single meaning and a meaning only represent a single term. Unfortunately, in Malay language there exists many terms that have multiple meanings and a single meaning that are represented by multiple terms. If these terms are treated as a single word, it will lead the search engine to retrieve irrelevant documents. These irrelevant documents retrieved will effect the effectiveness of the search engine. To investigate the enhancement of LSA using tagging algorithm (LSAT) in retrieving Malay documents, eight experiments are conducted in this research. The first experiment is conducted to compare the time taken for extracting normal term list and tagged term list, total number of both lists and also the time taken for the creation of term document matrix. Another six experiments record all the results of the LSA and LSAT search engine by using different dimension and threshold value. While the last experiment to compare the LSAT result with previous work on LSA using the same test collection. Outcomes of this study indicate that by using tagging algorithm, the recall value of the LSA algorithm can be enhanced up to 4% , the precision value also can be enhanced up to 16% and the F-measure value of LSA retrieval result can be enhanced by approximately up to 7% compared to LSA retrieval result without tagging algorithm. Furthermore, this research provides fundamental analyses to the other Information Retrieval (IR) developer in selecting the value of dimension and threshold value of retrieval that using LSA.
format	Thesis
qualification_level	Master's degree
author	Md Soom, Afiqah Bazlla
author_facet	Md Soom, Afiqah Bazlla
author_sort	Md Soom, Afiqah Bazlla
title	Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom
title_short	Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom
title_full	Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom
title_fullStr	Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom
title_full_unstemmed	Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom
title_sort	enhancing latent semantic analysis (lsa) using tagging algorithm in retrieving malay documents / afiqah bazlla md soom
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer Science and Mathematics
publishDate	2018
url	https://ir.uitm.edu.my/id/eprint/26905/1/TM_AFIQAH%20BAZLLA%20MD%20SOOM%20CS%2018_5.pdf
_version_	1783733916676390912

Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom

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