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Next Generation Data Technologies for Collective Computational Intelligence

Author: Nik Bessis

Publisher: Springer Science & Business Media

Published: 2011-04-28

Total Pages: 637

ISBN-13: 3642203434

This book focuses on next generation data technologies in support of collective and computational intelligence. The book brings various next generation data technologies together to capture, integrate, analyze, mine, annotate and visualize distributed data – made available from various community users – in a meaningful and collaborative for the organization manner. A unique perspective on collective computational intelligence is offered by embracing both theory and strategies fundamentals such as data clustering, graph partitioning, collaborative decision making, self-adaptive ant colony, swarm and evolutionary agents. It also covers emerging and next generation technologies in support of collective computational intelligence such as Web 2.0 social networks, semantic web for data annotation, knowledge representation and inference, data privacy and security, and enabling distributed and collaborative paradigms such as P2P, Grid and Cloud Computing due to the geographically dispersed and distributed nature of the data. The book aims to cover in a comprehensive manner the combinatorial effort of utilizing and integrating various next generations collaborative and distributed data technologies for computational intelligence in various scenarios. The book also distinguishes itself by assessing whether utilization and integration of next generation data technologies can assist in the identification of new opportunities, which may also be strategically fit for purpose.

Next Generation Data Technologies for Collective Computational Intelligence

Author: Nik Bessis

Publisher: Springer

Published: 2011-06-29

Total Pages: 637

ISBN-13: 3642203442

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New Trends in Computational Collective Intelligence

Author: David Camacho

Publisher: Springer

Published: 2014-09-10

Total Pages: 210

ISBN-13: 3319107747

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This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods and Applications, Computer Vision, and Intelligent Computational Methods. This book will be useful for graduate and PhD students in computer science as well as for mature academics, researchers and practitioners interested in the methods and applications of collective computational intelligence in order to create new intelligent systems.

Computational Collective Intelligence

Author: Manuel Núñez

Publisher: Springer

Published: 2015-09-09

Total Pages: 661

ISBN-13: 3319243063

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This two-volume set (LNAI 9329 and LNAI 9330) constitutes the refereed proceedings of the 7th International Conference on Collective Intelligence, ICCCI 2014, held in Madrid, Spain, in September 2015. The 110 full papers presented were carefully reviewed and selected from 186 submissions. They are organized in topical sections such as multi-agent systems; social networks and NLP; sentiment analysis; computational intelligence and games; ontologies and information extraction; formal methods and simulation; neural networks, SMT and MIS; collective intelligence in Web systems – Web systems analysis; computational swarm intelligence; cooperative strategies for decision making and optimization; advanced networking and security technologies; IT in biomedicine; collective computational intelligence in educational context; science intelligence and data analysis; computational intelligence in financial markets; ensemble learning; big data mining and searching.

Internet of Things and Big Data Technologies for Next Generation Healthcare

Author: Chintan Bhatt

Publisher: Springer

Published: 2017-01-01

Total Pages: 388

ISBN-13: 3319497367

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This comprehensive book focuses on better big-data security for healthcare organizations. Following an extensive introduction to the Internet of Things (IoT) in healthcare including challenging topics and scenarios, it offers an in-depth analysis of medical body area networks with the 5th generation of IoT communication technology along with its nanotechnology. It also describes a novel strategic framework and computationally intelligent model to measure possible security vulnerabilities in the context of e-health. Moreover, the book addresses healthcare systems that handle large volumes of data driven by patients’ records and health/personal information, including big-data-based knowledge management systems to support clinical decisions. Several of the issues faced in storing/processing big data are presented along with the available tools, technologies and algorithms to deal with those problems as well as a case study in healthcare analytics. Addressing trust, privacy, and security issues as well as the IoT and big-data challenges, the book highlights the advances in the field to guide engineers developing different IoT devices and evaluating the performance of different IoT techniques. Additionally, it explores the impact of such technologies on public, private, community, and hybrid scenarios in healthcare. This book offers professionals, scientists and engineers the latest technologies, techniques, and strategies for IoT and big data.

Computational Collective Intelligence -- Technologies and Applications

Author: Dosam Hwang

Publisher: Springer

Published: 2014-09-04

Total Pages: 723

ISBN-13: 3319112899

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This book constitutes the refereed proceedings of the 6th International Conference on Collective Intelligence, ICCCI 2014, held in Seoul, Korea, in September 2014. The 70 full papers presented were carefully reviewed and selected from 205 submissions. They address topics such as knowledge integration, data mining for collective processing, fuzzy, modal and collective systems, nature inspired systems, language processing systems, social networks and semantic web, agent and multi-agent systems, classification and clustering methods, multi-dimensional data processing, Web systems, intelligent decision making, methods for scheduling, image and video processing, collective intelligence in web systems, computational swarm intelligence, cooperation and collective knowledge.

Computational Collective Intelligence

Author: Manuel Núñez

Publisher: Springer

Published: 2015-09-09

Total Pages: 515

ISBN-13: 3319240692

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Big Data and Internet of Things

Author: Nik Bessis

Publisher:

Published: 2014-03-31

Total Pages: 492

ISBN-13: 9783319050300

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Data-Driven Modelling and Predictive Analytics in Business and Finance

Author: Alex Khang

Publisher: CRC Press

Published: 2024-07-24

Total Pages: 443

ISBN-13: 1040088465

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Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent. Data- Driven Modelling and Predictive Analytics in Business and Finance covers the need for intelligent business solutions and applications. Explaining how business applications use algorithms and models to bring out the desired results, the book covers: Data-driven modelling Predictive analytics Data analytics and visualization tools AI-aided applications Cybersecurity techniques Cloud computing IoT-enabled systems for developing smart financial systems This book was written for business analysts, financial analysts, scholars, researchers, academics, professionals, and students so they may be able to share and contribute new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices.

Multimodal Analytics for Next-Generation Big Data Technologies and Applications

Author: Kah Phooi Seng

Publisher: Springer

Published: 2019-07-18

Total Pages: 391

ISBN-13: 3319975986

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This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal data; unsupervised learning strategies for big multimodal data; supervised learning strategies for big multimodal data; and multimodal big data processing and applications. The book will be of value to researchers, professionals and students in engineering and computer science, particularly those engaged with image and speech processing, multimodal information processing, data science, and artificial intelligence.