A novel algorithm with IM-LSI index for incremental maintenance of materialized view

The ability to afford decision makers with both accurate and timely consolidated information as well as rapid query response times is the fundamental requirement for the success of a Data Warehouse. To provide fast access, a data warehouse stores materialized views of the sources of its data. As a r...

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Detalles Bibliográficos
Autores principales: Rangarajan, K., Kumaravel, A., Nalini, T.
Formato: Articulo
Lenguaje:Inglés
Publicado: 2012
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/9712
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr12-6.pdf
Aporte de:
id I19-R120-10915-9712
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Informática
I-mine item set index
FP growth
LSI index
Data warehouse and repository
spellingShingle Informática
I-mine item set index
FP growth
LSI index
Data warehouse and repository
Rangarajan, K.
Kumaravel, A.
Nalini, T.
A novel algorithm with IM-LSI index for incremental maintenance of materialized view
topic_facet Informática
I-mine item set index
FP growth
LSI index
Data warehouse and repository
description The ability to afford decision makers with both accurate and timely consolidated information as well as rapid query response times is the fundamental requirement for the success of a Data Warehouse. To provide fast access, a data warehouse stores materialized views of the sources of its data. As a result, a data warehouse needs to be maintained to keep its contents consistent with the contents of its data sources. Incremental maintenance is generally regarded as a more efficient way to maintain materialized views in a data warehouse The view has to be maintained to reflect the updates done against the base relations stored at the various distributed data sources. The proposed approach contains two modules namely, materialized view selection(MVS) and maintenance of materialized view. (MMV). In recent times, several algorithms have been proposed for keeping the views up-to-date in response to the changes in the source data. Therefore, we present an improved algorithm for MVS and MMV using IM-LSI(Itemset Mining using Latent Semantic Index) algorithm. selection of views to materialize using the IM(Itemset Mining) algorithm method to overcome the problem resulting from conventional view selection algorithms and then we consider the maintenance of materialized views using LSI. For the justification of the proposed algorithm, we reveal the experimental results in which both time and space costs better than conventional algorithms.
format Articulo
Articulo
author Rangarajan, K.
Kumaravel, A.
Nalini, T.
author_facet Rangarajan, K.
Kumaravel, A.
Nalini, T.
author_sort Rangarajan, K.
title A novel algorithm with IM-LSI index for incremental maintenance of materialized view
title_short A novel algorithm with IM-LSI index for incremental maintenance of materialized view
title_full A novel algorithm with IM-LSI index for incremental maintenance of materialized view
title_fullStr A novel algorithm with IM-LSI index for incremental maintenance of materialized view
title_full_unstemmed A novel algorithm with IM-LSI index for incremental maintenance of materialized view
title_sort novel algorithm with im-lsi index for incremental maintenance of materialized view
publishDate 2012
url http://sedici.unlp.edu.ar/handle/10915/9712
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr12-6.pdf
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