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Fast Decision Tree To Index Large DNA-Protein Sequence Datasets: Adapting and Enhancing the Searching Algorithm Based on Decision Tree Indexing for Large DNA-Protein Datasets - Softcover
Synopsis
The significant growth in biological data has motivated important research by computer scientists into creating fast and accurate algorithms for accessing the database at the fastest possible rates. Therefore, there still remains the need for an efficient indexing approach to speed up the searching time for large biological data, to help the biologists to retrieve the exiting information quickly, from any biological database. Furthermore, the trends in parallel programming models has also encouraged the computer researchers to improve the indexing approaches to cope with this exponential increase. This book adopted a Decision Tree method as an Indexing Model (DTIM), to allow for large databases to be processed. This method of indexing could effectively and rapidly retrieve all similar DNA-Proteins data from a large database for a given query. The decision tree indexing model (PDTIM) was then parallelized, using a hybrid of distributed and shared memory to accelerate the index building time. Finally, to improve the accuracy rate for decision tree algorithm, the decision tree was hybridized with a harmony search algorithm (HDT-HS).
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About the Author
Khalid Mohammad Jaber received his BSc Degree in Computer Science from Isra University,Jordan in 2005 and Master Degree and PhD in Computer Science from Universiti Sains Malaysia, Malaysia in 2007 and 2011 respectively.He is currently a assistant professor at Faculty of Science and Information Technology, Al-Zaytoonah University of Jordan.
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Fast Decision Tree To Index Large DNA-Protein Sequence Datasets
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LAP LAMBERT Academic Publishing Okt 2012, 2012
ISBN 10: 3659254762
ISBN 13: 9783659254765
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The significant growth in biological data has motivated important research by computer scientists into creating fast and accurate algorithms for accessing the database at the fastest possible rates. Therefore, there still remains the need for an efficient indexing approach to speed up the searching time for large biological data, to help the biologists to retrieve the exiting information quickly, from any biological database. Furthermore, the trends in parallel programming models has also encouraged the computer researchers to improve the indexing approaches to cope with this exponential increase. This book adopted a Decision Tree method as an Indexing Model (DTIM), to allow for large databases to be processed. This method of indexing could effectively and rapidly retrieve all similar DNA-Proteins data from a large database for a given query. The decision tree indexing model (PDTIM) was then parallelized, using a hybrid of distributed and shared memory to accelerate the index building time. Finally, to improve the accuracy rate for decision tree algorithm, the decision tree was hybridized with a harmony search algorithm (HDT-HS). 196 pp. Englisch. Seller Inventory # 9783659254765
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Fast Decision Tree To Index Large DNA-Protein Sequence Datasets
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ISBN 13: 9783659254765
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jaber Khalid MohammadKhalid Mohammad Jaber received his BSc Degree in Computer Science from Isra University,Jordan in 2005 and Master Degree and PhD in Computer Science from Universiti Sains Malaysia, Malaysia in 2007 and 2011 respe. Seller Inventory # 5143398
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Fast Decision Tree To Index Large DNA-Protein Sequence Datasets : Adapting and Enhancing the Searching Algorithm Based on Decision Tree Indexing for Large DNA-Protein Datasets
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LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659254762
ISBN 13: 9783659254765
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The significant growth in biological data has motivated important research by computer scientists into creating fast and accurate algorithms for accessing the database at the fastest possible rates. Therefore, there still remains the need for an efficient indexing approach to speed up the searching time for large biological data, to help the biologists to retrieve the exiting information quickly, from any biological database. Furthermore, the trends in parallel programming models has also encouraged the computer researchers to improve the indexing approaches to cope with this exponential increase. This book adopted a Decision Tree method as an Indexing Model (DTIM), to allow for large databases to be processed. This method of indexing could effectively and rapidly retrieve all similar DNA-Proteins data from a large database for a given query. The decision tree indexing model (PDTIM) was then parallelized, using a hybrid of distributed and shared memory to accelerate the index building time. Finally, to improve the accuracy rate for decision tree algorithm, the decision tree was hybridized with a harmony search algorithm (HDT-HS). Seller Inventory # 9783659254765
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Fast Decision Tree To Index Large DNA-Protein Sequence Datasets: Adapting and Enhancing the Searching Algorithm Based on Decision Tree Indexing for Large DNA-Protein Datasets
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ISBN 13: 9783659254765
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Fast Decision Tree To Index Large DNA-Protein Sequence Datasets: Adapting and Enhancing the Searching Algorithm Based on Decision Tree Indexing for Large DNA-Protein Datasets
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ISBN 10: 3659254762
ISBN 13: 9783659254765
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Fast Decision Tree To Index Large DNA-Protein Sequence Datasets: Adapting and Enhancing the Searching Algorithm Based on Decision Tree Indexing for Large DNA-Protein Datasets
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ISBN 10: 3659254762
ISBN 13: 9783659254765
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Fast Decision Tree To Index Large DNA-Protein Sequence Datasets
Published by
LAP LAMBERT Academic Publishing Okt 2012, 2012
ISBN 10: 3659254762
ISBN 13: 9783659254765
New
Taschenbuch
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The significant growth in biological data has motivated important research by computer scientists into creating fast and accurate algorithms for accessing the database at the fastest possible rates. Therefore, there still remains the need for an efficient indexing approach to speed up the searching time for large biological data, to help the biologists to retrieve the exiting information quickly, from any biological database. Furthermore, the trends in parallel programming models has also encouraged the computer researchers to improve the indexing approaches to cope with this exponential increase. This book adopted a Decision Tree method as an Indexing Model (DTIM), to allow for large databases to be processed. This method of indexing could effectively and rapidly retrieve all similar DNA-Proteins data from a large database for a given query. The decision tree indexing model (PDTIM) was then parallelized, using a hybrid of distributed and shared memory to accelerate the index building time. Finally, to improve the accuracy rate for decision tree algorithm, the decision tree was hybridized with a harmony search algorithm (HDT-HS).OmniScriptum SRL, Str. Armeneasca 28/1, office 1, 2012 Chisinau 196 pp. Englisch. Seller Inventory # 9783659254765
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Fast Decision Tree To Index Large DNA-Protein Sequence Datasets | Adapting and Enhancing the Searching Algorithm Based on Decision Tree Indexing for Large DNA-Protein Datasets
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LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659254762
ISBN 13: 9783659254765
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Taschenbuch. Condition: Neu. Fast Decision Tree To Index Large DNA-Protein Sequence Datasets | Adapting and Enhancing the Searching Algorithm Based on Decision Tree Indexing for Large DNA-Protein Datasets | Khalid Mohammad Jaber | Taschenbuch | 196 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659254765 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 106213103