Description
Taylor & Francis Big Data Algorithms Analytics And Applications by Kuan-Ching Li
As today's organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages._x000D__x000D_Presenting the contributions of leading experts in their respective fields, Big Data: Algorithms, Analytics, and Applications bridges the gap between the vastness of Big Data and the appropriate computational methods for scientific and social discovery. It covers fundamental issues about Big Data, including efficient algorithmic methods to process data, better analytical strategies to digest data, and representative applications in diverse fields, such as medicine, science, and engineering. The book is organized into five main sections:_x000D__x000D__x000D__x000D__x000D_Big Data Management-considers the research issues related to the management of Big Data, including indexing and scalability aspects_x000D_Big Data Processing-addresses the problem of processing Big Data across a wide range of resource-intensive computational settings_x000D_Big Data Stream Techniques and Algorithms-explores research issues regarding the management and mining of Big Data in streaming environments_x000D_Big Data Privacy-focuses on models, techniques, and algorithms for preserving Big Data privacy_x000D_Big Data Applications-illustrates practical applications of Big Data across several domains, including finance, multimedia tools, biometrics, and satellite Big Data processing_x000D__x000D__x000D__x000D__x000D__x000D_Overall, the book reports on state-of-the-art studies and achievements in algorithms, analytics, and applications of Big Data. It provides readers with the basis for further efforts in this challenging scientific field that will play a leading role in next-generation database, data warehousing, data mining, and cloud computing research. It also explores related applications in diverse sectors, covering technologies for media/data communication, elastic media/data storage, cross-network media/data fusion, and SaaS._x000D_ _x000D_
Scalable Indexing for Big Data Processing; Hisham Mohamed and Stephane Marchand-Maillet_x000D_
Scalability and Cost Evaluation of Incremental Data Processing using Amazon's Hadoop Service; Xing Wu, Yan Liu, and Ian Gorton_x000D_
Singular Value Decomposition, Clustering, and Indexing for Similarity Search for Large Data Sets in High-Dimensional Spaces; Alexander Thomasian_x000D_
Multiple Sequence Alignment and Clustering with Dot Matrices, Entropy, and Genetic Algorithms; John Tsiligaridis_x000D_
Approaches for High-Performance Big Data Processing: Applications and Challenges; Ouidad Achahbar, Mohamed Riduan Abid, Mohamed Bakhouya, Chaker El Amrani, Jaafar Gaber, Mohammed Essaaidi, and Tarek A. El Ghazawi_x000D_
The Art of Scheduling for Big Data Science; Florin Pop and Valentin Cristea_x000D_
Time-Space Scheduling in the MapReduce Framework; Zhuo Tang, Lingang Jiang, Ling Qi, Kenli Li, and Keqin Li_x000D_
The Graph Engine for Multithreaded Systems Graph Database System for Commodity Clusters; Alessandro Morari, Vito Giovanni Caltellana, Oreste Villa, Jesse Weaver, Greg Williams, David Haglin, Antonino Tumeo, and John Feo_x000D_
KSC-net: Community Detection for Big Data Networks; Raghvendra Mall and Johan A.K. Suykens_x000D_
Making Big Data Transparent to the Software Developers' Community; Yu Wu, Jessica Kropczynski, and John M. Carroll_x000D_
Key Technologies for Big Data Stream Computing; Dawei Sun, Guangyan Zhang, Weimin Zheng, and Keqin Li_x000D_
Streaming Algorithms for Big Data Processing on Multicore Architecture; Marat Zhanikeev_x000D_
Organic Streams: A Unified Framework for Personal Big Data Integration and Organization Towards Social Sharing and Individualized Sustainable Use; Xiaokang Zhou and Qun Jin_x000D_
Managing Big Trajectory Data: Online Processing of Positional Streams; Kostas Patroumpas and Timos Sellis_x000D_
Personal Data Protection Aspects of Big Data; Paolo Balboni_x000D_
Privacy-Preserving Big Data Management: The Case of OLAP; Alfredo Cuzzocrea_x000D_
Big Data in Finance; Taruna Seth and Vipin Chaudhary_x000D_
Semantic-Based Heterogeneous Multimedia Big Data Retrieval; Kehua Guo and Jianhua Ma_x000D_
Topic Modeling for Large-Scale Multimedia Analysis and Retrieval; Juan Hu, Yi Fang, Nam Ling, and Li Song_x000D_
Big Data Biometrics Processing: A Case Study of an Iris Matching Algorithm on Intel Xeon Phi; Xueyan Li and Chen Liu_x000D_
Storing, Managing, and Analyzing Big Satellite Data: Experiences and Lessons Learned from a Real-World Application; Ziliang Zong_x000D_
Barriers to the Adoption of Big-Data Applications in the Social Sector; Elena Strange_x000D_