Transactions on Computational Collective Intelligence XXXVI

This issue of the journal focuses on computer-based methods of computational collective intelligence (CCI) and their applications in various fields, including performance optimization in IoT, big data, reliability, privacy, security, service selection, QoS, and machine learning. The 7 selected papers present new findings, innovative methodologies, and discussions on challenges in the field, aiming to achieve QoS for final users.

Format: Paperback / softback
Length: 161 pages
Publication date: 05 December 2021
Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

These transactions publish research on computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields, including performance optimization in IoT, big data, reliability, privacy, security, service selection, QoS, and machine learning. This 36th issue contains 7 selected papers that present new findings, innovative methodologies, and discuss issues and challenges in the field of collective intelligence from big data and networking paradigms, while addressing security, privacy, reliability, and optimality to achieve QoS to the benefit of final users. This is an open-access book.

Introduction:
Collective intelligence (CI) has gained significant attention in recent years due to its potential to solve complex problems and optimize decision-making processes. CI refers to the ability of groups of individuals to collaborate and generate insights that are greater than the sum of their individual abilities. There are many different approaches to CI, including computer-based methods of computational collective intelligence (CCI). CCI is a subfield of artificial intelligence that focuses on developing algorithms and systems that can leverage the collective intelligence of groups of individuals.

Scope of Research:
CCI research covers a wide range of fields, including performance optimization in IoT, big data, reliability, privacy, security, service selection, QoS, and machine learning. IoT refers to the network of physical devices that are connected to the internet and can communicate with each other. Big data refers to the large amounts of data that are generated by these devices and can be used to analyze and make predictions. Reliability refers to the ability of a system or device to perform its intended function correctly and consistently. Privacy refers to the protection of personal information and data. Security refers to the prevention of unauthorized access to sensitive information and data. Service selection refers to the process of selecting the best service or product for a particular user or application. QoS refers to the quality of service that a system or device provides to its users. Machine learning refers to the use of algorithms and statistical models to analyze and predict data.

Selected Papers:
This 36th issue of the transactions contains 7 selected papers that present new findings and innovative methodologies as well as discuss issues and challenges in the field of collective intelligence from big data and networking paradigms while addressing security, privacy, reliability, and optimality to achieve QoS to the benefit of final users.

Conclusion:
CCI research has the potential to revolutionize the way we solve complex problems and optimize decision-making processes. By leveraging the collective intelligence of groups of individuals, we can achieve better outcomes and make more informed decisions. However, there are still many challenges to be addressed in the field, including the development of more effective algorithms and systems, the integration of different technologies, and the establishment of ethical guidelines and policies.

Weight: 279g
Dimension: 235 x 155 (mm)
ISBN-13: 9783662645628
Edition number: 1st ed. 2021