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Advanced metaheuristic methods in big data retrieval and analytics

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Advanced metaheuristic methods in big data retrieval and analytics/ Hadj Ahmed Bouarara, Reda Mohamed Hamou, and Amine Rahmani, editors.
other author:	Bouarara, Hadj Ahmed,
Published:	Hershey, Pennsylvania :IGI Global, : [2019],
Description:	1 online resource (xx, 320 p.)
Subject:	Big data. -
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-7338-8
ISBN:	9781522573395 (e-book)

Advanced metaheuristic methods in big data retrieval and analytics
Advanced metaheuristic methods in big data retrieval and analytics[electronic resource] /Hadj Ahmed Bouarara, Reda Mohamed Hamou, and Amine Rahmani, editors. - Hershey, Pennsylvania :IGI Global,[2019] - 1 online resource (xx, 320 p.)

Includes bibliographical references and index.

Chapter 1. A comprehensive study on internet of things based on key artificial intelligence technologies and industry 4.0 -- Chapter 2. Ecological data exploration -- Chapter 3. Context of the person in social networks -- Chapter 4. Study on the different forms of plagiarism in textual data and image: internal and external detection -- Chapter 5. Enrichment ontology via linked data -- Chapter 6. Big data and privacy state of the art -- Chapter 7. Cardiovascular disease prediction using data mining techniques: a proposed framework using big data approach -- Chapter 8. Classification and machine learning -- Chapter 9. Clear and private ad hoc retrieval models on Web data -- Chapter 10. Spam filtering and detection: state of the art and overview -- Chapter 11. Security in wireless sensor networks: Sybil attack detection and prevention -- Chapter 12. Hybridization of biogeography-based optimization and gravitational search algorithm for efficient face recognition.

Restricted to subscribers or individual electronic text purchasers.

"This book focuses on new advancements of exploration, creation and development of metaheuristic algorithms in information retrieval models over big data environment and services. It presents how metaheuristics could affect in good or bad the results of different retrieval models and the impact of applying it in such complex and huge environment like big data"--Provided by publisher.

ISBN: 9781522573395 (e-book)Subjects--Topical Terms:

981821
Big data.

LC Class. No.: QA76.9.B45 / A34 2019e

Dewey Class. No.: 005.7

Advanced metaheuristic methods in big data retrieval and analytics
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050 0 0 $a QA76.9.B45 $b A34 2019e
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245 0 0 $a Advanced metaheuristic methods in big data retrieval and analytics $h [electronic resource] / $c Hadj Ahmed Bouarara, Reda Mohamed Hamou, and Amine Rahmani, editors.
260 $a Hershey, Pennsylvania : $b IGI Global, $c [2019]
300 $a 1 online resource (xx, 320 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. A comprehensive study on internet of things based on key artificial intelligence technologies and industry 4.0 -- Chapter 2. Ecological data exploration -- Chapter 3. Context of the person in social networks -- Chapter 4. Study on the different forms of plagiarism in textual data and image: internal and external detection -- Chapter 5. Enrichment ontology via linked data -- Chapter 6. Big data and privacy state of the art -- Chapter 7. Cardiovascular disease prediction using data mining techniques: a proposed framework using big data approach -- Chapter 8. Classification and machine learning -- Chapter 9. Clear and private ad hoc retrieval models on Web data -- Chapter 10. Spam filtering and detection: state of the art and overview -- Chapter 11. Security in wireless sensor networks: Sybil attack detection and prevention -- Chapter 12. Hybridization of biogeography-based optimization and gravitational search algorithm for efficient face recognition.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "This book focuses on new advancements of exploration, creation and development of metaheuristic algorithms in information retrieval models over big data environment and services. It presents how metaheuristics could affect in good or bad the results of different retrieval models and the impact of applying it in such complex and huge environment like big data"--Provided by publisher.
650 0 $a Big data. $3 981821
650 0 $a Metaheuristics. $3 1164261
700 1 $a Bouarara, Hadj Ahmed, $d 1990- $e editor. $3 1235010
700 1 $a Hamou, Reda Mohamed, $d 1967- $e editor. $3 1155988
700 1 $a Rahmani, Amine, $d 1991- $e editor. $3 1235011
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-7338-8