Advanced Metaheuristic Methods in Big Data Retrieval and Analytics
Language: English
Published by Engineering Science Reference, 2018
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Condition: New
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Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - The amount of data shared and stored on the web and other document repositories is steadily on the rise. Unfortunately, this growth increases inefficiencies and difficulties when trying to find the most relevant and up-to-date information due to unstructured data. Advanced Metaheuristic Methods in Big Data Retrieval and Analytics examines metaheuristic techniques as an important alternative model for solving complex problems that are not treatable by deterministic methods. Recent studies suggest that IR and biomimicry can be used together for several application problems in big data and internet of things, especially when conventional methods would be too expensive or difficult to implement. Featuring coverage on a broad range of topics such as ontology, plagiarism detection, and machine learning, this book is ideally designed for engineers, graduate students, IT professionals, and academicians seeking an overview of new trends in information retrieval in big data.…
Seller Inventory # 9781522587187
- Title
- Advanced Metaheuristic Methods in Big Data Retrieval and Analytics
- Author
- Reda Mohamed Hamou
- Publisher
- Engineering Science Reference
- Publication year
- 2018
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1522587187
- ISBN 13
- 9781522587187
- Item weight
- 655 grams
- Dimensions
- 254x178x19 mm
Advanced Metaheuristic Methods in Big Data Retrieval and Analytics examines metaheuristic techniques as an important alternative model for solving complex problems that are not treatable by deterministic methods. Recent studies suggest that IR and biomimicry can be used together for several application problems in big data and internet of things, especially when conventional methods would be too expensive or difficult to implement. Featuring coverage on a broad range of topics such as ontology, plagiarism detection, and machine learning, this book is ideally designed for engineers, graduate students, IT professionals, and academicians seeking an overview of new trends in information retrieval in big data.
"Synopsis" may belong to another edition of this title.
About the Author
Reda Mohamed Hamou received an engineering degree in computer Science from the Computer Science department of Djillali Liabes University of Sidi-Belabbes-Algeria and PhD (Artificial intelligence) from the same University. He has several publications in the field of BioInspired and Metaheuristic in many journals as IJAMC, IJIRR, IJAEC, IJALR, IJISP, IJIIT, JITR, IJCINI, IJOCI, IJSIR, IJSI, IJAEIS, IJDSST, IJBRA, Applied Inteligence,.... His research interests include Data Mining, Text Mining, Classification, Clustering, computational intelligence, neural networks, evolutionary computation and Biomimetic optimization method. He is a head of research team in GecoDe laboratory. Dr. Hamou is an associate professor in technology faculty in UTMS University of Saida-Algeria.
Amine Rahmani received a licence degree in computer Science from the Computer Science department of Dr. Tahar Moulay University of Saida-Algeria, received the Master diploma in Network, System and Security Informatics from Djillali Liabes University. Now Amine RAHMANI is a phd student in Web and Knowledge Engineering in Dr. Tahar Moulay University. His research interests include Big Data, Privacy Preserving, Informatics Security, Data Mining, Cloud Computing, Big Data analytics, Access Control, and Cryptography.
"About the title" may belong to another edition of this title.
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