Synopsis
There are many benefits from using data compression, like saving space on hard drives or lowering the use of transmission bandwidth in the network. In this work two intelligent techniques are used as lossless data compression algorithms; namely, clustering and association rules techniques. In the first stage, the database is compressed by using a clustering technique followed by association rules algorithm. The first technique partitions the data that exist in the database file and save these data as clusters by using the adaptive k-means algorithm while the second technique extracts the important rules from each cluster using the apriori algorithm. Several experiments are made in several different sizes of database. The experiments show that using the adaptive k-means algorithm and apriori algorithm together give better compression ratio and smaller compressed file size. The apriori algorithm increases the compression ratio of the adaptive k-means algorithm when they are used together.
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Using Clustering and Association Rules Techniques
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LAP LAMBERT Academic Publishing Okt 2019, 2019
ISBN 10: 6134979031
ISBN 13: 9786134979030
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -There are many benefits from using data compression, like saving space on hard drives or lowering the use of transmission bandwidth in the network. In this work two intelligent techniques are used as lossless data compression algorithms; namely, clustering and association rules techniques. In the first stage, the database is compressed by using a clustering technique followed by association rules algorithm. The first technique partitions the data that exist in the database file and save these data as clusters by using the adaptive k-means algorithm while the second technique extracts the important rules from each cluster using the apriori algorithm. Several experiments are made in several different sizes of database. The experiments show that using the adaptive k-means algorithm and apriori algorithm together give better compression ratio and smaller compressed file size. The apriori algorithm increases the compression ratio of the adaptive k-means algorithm when they are used together. 140 pp. Englisch. Seller Inventory # 9786134979030
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Using Clustering and Association Rules Techniques
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Subhi Ali Dr. RashaRasha Subhi Ali is Doctor in Computer Science in University of Technology. Prof. Dr. Ahmed T. Sadiq is Doctor in Computer Science in University of Technology.Dr. Mehdi G. Duaimi is Doctor in Computer Science in Bag. Seller Inventory # 335815746
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Using Clustering and Association Rules Techniques
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LAP LAMBERT Academic Publishing Okt 2019, 2019
ISBN 10: 6134979031
ISBN 13: 9786134979030
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -There are many benefits from using data compression, like saving space on hard drives or lowering the use of transmission bandwidth in the network. In this work two intelligent techniques are used as lossless data compression algorithms; namely, clustering and association rules techniques. In the first stage, the database is compressed by using a clustering technique followed by association rules algorithm. The first technique partitions the data that exist in the database file and save these data as clusters by using the adaptive k-means algorithm while the second technique extracts the important rules from each cluster using the apriori algorithm. Several experiments are made in several different sizes of database. The experiments show that using the adaptive k-means algorithm and apriori algorithm together give better compression ratio and smaller compressed file size. The apriori algorithm increases the compression ratio of the adaptive k-means algorithm when they are used together.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch. Seller Inventory # 9786134979030
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Using Clustering and Association Rules Techniques | To Compress Data Sets
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Taschenbuch. Condition: Neu. Using Clustering and Association Rules Techniques | To Compress Data Sets | Rasha Subhi Ali (u. a.) | Taschenbuch | 140 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786134979030 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 117815599
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Using Clustering and Association Rules Techniques : To Compress Data Sets
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - There are many benefits from using data compression, like saving space on hard drives or lowering the use of transmission bandwidth in the network. In this work two intelligent techniques are used as lossless data compression algorithms; namely, clustering and association rules techniques. In the first stage, the database is compressed by using a clustering technique followed by association rules algorithm. The first technique partitions the data that exist in the database file and save these data as clusters by using the adaptive k-means algorithm while the second technique extracts the important rules from each cluster using the apriori algorithm. Several experiments are made in several different sizes of database. The experiments show that using the adaptive k-means algorithm and apriori algorithm together give better compression ratio and smaller compressed file size. The apriori algorithm increases the compression ratio of the adaptive k-means algorithm when they are used together. Seller Inventory # 9786134979030
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