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...

Full description

Bibliographic Details
Main Author:	Md Soom, Afiqah Bazlla
Format:	Thesis
Language:	English
Published:	2018
Subjects:	Analysis Algorithms
Online Access:	http://ir.uitm.edu.my/id/eprint/26905/ http://ir.uitm.edu.my/id/eprint/26905/1/TM_AFIQAH%20BAZLLA%20MD%20SOOM%20CS%2018_5.pdf

id	uitm-26905
recordtype	eprints
spelling	uitm-269052019-12-16T06:35:07Z http://ir.uitm.edu.my/id/eprint/26905/ Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom 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 NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/26905/1/TM_AFIQAH%20BAZLLA%20MD%20SOOM%20CS%2018_5.pdf Md Soom, Afiqah Bazlla (2018) Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom. Masters thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
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
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
publishDate	2018
url	http://ir.uitm.edu.my/id/eprint/26905/ http://ir.uitm.edu.my/id/eprint/26905/1/TM_AFIQAH%20BAZLLA%20MD%20SOOM%20CS%2018_5.pdf
first_indexed	2023-09-18T23:17:34Z
last_indexed	2023-09-18T23:17:34Z
_version_	1777419214596866048

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

Similar Items