THE USE OF SINGULAR VALUE DECOMPOSITION (SVD) ON LATENT SEMANTIC INDEXING (LSI) FOR INFORMATION RETRIEVAL

THE USE OF SINGULAR VALUE DECOMPOSITION (SVD) ON LATENT SEMANTIC INDEXING (LSI) FOR INFORMATION RETRIEVAL

Lately the approach to get a subject on written form from science data base depend on the match between words which used by user and the words which placed in the data base. It causes the variety of words which used to describe the same document. By using Singular Value Decomposition, which is deter...

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Main Author: SRI MULYATI (NIM 20107056), ETI
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/12082
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:12082
spelling id-itb.:120822017-09-27T14:41:47ZTHE USE OF SINGULAR VALUE DECOMPOSITION (SVD) ON LATENT SEMANTIC INDEXING (LSI) FOR INFORMATION RETRIEVAL SRI MULYATI (NIM 20107056), ETI Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/12082 Lately the approach to get a subject on written form from science data base depend on the match between words which used by user and the words which placed in the data base. It causes the variety of words which used to describe the same document. By using Singular Value Decomposition, which is determine SVD from matrix term generally with referred document, there is an advantage in obtaining information from hidden document. The terms and the documents are represented by singular vector which subsequently matched with the user words. The retrieval method is called latent semantic indexing (LSI). By LSI the important connection between terms and documents are acquired. LSI is a method that widely could be applied, and could increase the access of the user to the information which is in written forms or documents or services which provide a describe on text. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Lately the approach to get a subject on written form from science data base depend on the match between words which used by user and the words which placed in the data base. It causes the variety of words which used to describe the same document. By using Singular Value Decomposition, which is determine SVD from matrix term generally with referred document, there is an advantage in obtaining information from hidden document. The terms and the documents are represented by singular vector which subsequently matched with the user words. The retrieval method is called latent semantic indexing (LSI). By LSI the important connection between terms and documents are acquired. LSI is a method that widely could be applied, and could increase the access of the user to the information which is in written forms or documents or services which provide a describe on text.
format Theses
author SRI MULYATI (NIM 20107056), ETI
spellingShingle SRI MULYATI (NIM 20107056), ETI
THE USE OF SINGULAR VALUE DECOMPOSITION (SVD) ON LATENT SEMANTIC INDEXING (LSI) FOR INFORMATION RETRIEVAL
author_facet SRI MULYATI (NIM 20107056), ETI
author_sort SRI MULYATI (NIM 20107056), ETI
title THE USE OF SINGULAR VALUE DECOMPOSITION (SVD) ON LATENT SEMANTIC INDEXING (LSI) FOR INFORMATION RETRIEVAL
title_short THE USE OF SINGULAR VALUE DECOMPOSITION (SVD) ON LATENT SEMANTIC INDEXING (LSI) FOR INFORMATION RETRIEVAL
title_full THE USE OF SINGULAR VALUE DECOMPOSITION (SVD) ON LATENT SEMANTIC INDEXING (LSI) FOR INFORMATION RETRIEVAL
title_fullStr THE USE OF SINGULAR VALUE DECOMPOSITION (SVD) ON LATENT SEMANTIC INDEXING (LSI) FOR INFORMATION RETRIEVAL
title_full_unstemmed THE USE OF SINGULAR VALUE DECOMPOSITION (SVD) ON LATENT SEMANTIC INDEXING (LSI) FOR INFORMATION RETRIEVAL
title_sort use of singular value decomposition (svd) on latent semantic indexing (lsi) for information retrieval
url https://digilib.itb.ac.id/gdl/view/12082
_version_ 1820728406929571840

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