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This book constitutes refereed proceedings of the 13th International Conference on International Conference on Computational Collective Intelligence, ICCCI 2021, held in Kallithea, Rhodes, Greece, in October - November 2021. Due to the the COVID-19 pandemic the conference was held online. The 44 full papers and 14 short papers were thoroughly reviewed and selected from 231 submissions. The papers are organized according to the following topical sections: social networks and recommender systems; collective decision-making; computer vision techniques; innovations in intelligent systems; cybersecurity intelligent methods; data mining and machine learning; machine learning in real-world data; Internet of Things and computational technologies for collective intelligence; smart industry and management systems; low resource languages processing; computational intelligence for multimedia understanding.
This book constitutes the refereed proceedings of the 15th International Conference on Advances in Computational Collective Intelligence, ICCCI 2023, held in Budapest, Hungary, during September 27–29, 2023. The 59 full papers included in this book were carefully reviewed and selected from 218 submissions. They were organized in topical sections as follows: Collective Intelligence and Collective Decision-Making, Deep Learning Techniques, Natural Language Processing, Data Minning and Machine learning, Social Networks and Speek Communication, Cybersecurity and Internet of Things, Cooperative Strategies for Decision Making and Optimization, Digital Content Understanding and Apllication for Industry 4.0 and Computational Intelligence in Medical Applications.
This book constitutes refereed proceedings of the 14th International Conference on International Conference on Computational Collective Intelligence, ICCCI 2022, held in Hammamet, Tunisia, in September 2022. The 43 full papers and 15 short papers were thoroughly reviewed and selected from 421 submissions. The papers are grouped in topical sections on collective intelligence and collective decision-making; natural language processing; deep learning; computational intelligence for multimedia understanding; computational intelligence in medical applications; applications for industry 4.0; experience enhanced intelligence to IoT and sensors; cooperative strategies for decision making and optimization; machine learning methods.
This volume constitutes the refereed proceedings of the 12th International Conference on Computational Collective Intelligence, ICCCI 2020, held in Da Nang, Vietnam, in November 2020.* The 70 full papers presented were carefully reviewed and selected from 314 submissions. The papers are grouped in topical sections on: knowledge engineering and semantic web; social networks and recommender systems; collective decision-making; applications of collective intelligence; data mining methods and applications; machine learning methods; deep learning and applications for industry 4.0; computer vision techniques; biosensors and biometric techniques; innovations in intelligent systems; natural language processing; low resource languages processing; computational collective intelligence and natural language processing; computational intelligence for multimedia understanding; and intelligent processing of multimedia in web systems. *The conference was held virtually due to the COVID-19 pandemic.
This book constitutes refereed proceedings of the 12th International Conference on International Conference on Computational Collective Intelligence, ICCCI 2020, held in Da Nang, Vietnam, in November – December 2020. Due to the the COVID-19 pandemic the conference was held online. The 68 papers were thoroughly reviewed and selected from 314 submissions. The papers are organized according to the following topical sections: data mining and machine learning; deep learning and applications for industry 4.0; recommender systems; computer vision techniques; decision support and control systems; intelligent management information systems; innovations in intelligent systems; intelligent modeling and simulation approaches for games and real world systems; experience enhanced intelligence to IoT; data driven IoT for smart society; applications of collective intelligence; natural language processing; low resource languages processing; computational collective intelligence and natural language processing.
The book consists of 35 extended chapters which have been selected and invited from the submissions to the 4th International Conference on Computational Collective Intelligence Technologies and Applications (ICCCI 2012) held on November 28-30, 2012 in Ho Chi Minh City, Vietnam. The book is organized into six parts, which are semantic web and ontologies, social networks and e-learning, agent and multiagent systems, data mining methods and applications, soft computing, and optimization and control, respectively. All chapters in the book discuss theoretical and practical issues connected with computational collective intelligence and related technologies. The editors hope that the book can be useful for graduate and Ph.D. students in Computer Science, in particular participants in courses on Soft Computing, Multiagent Systems, and Data Mining. This book can be also useful for researchers working on the concept of computational collective intelligence in artificial populations. It is the hope of the editors that readers of this volume can find many inspiring ideas and use them to create new cases of intelligent collectives. Many such challenges are suggested by particular approaches and models presented in individual chapters of this book. The editors hope that readers of this volume can find many inspiring ideas and influential practical examples and use them in their future work.
Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains: Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details." -- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths." -- Tim Wolters, CTO, Collective Intellect
These Transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the Semantic Web, social networks and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This fourth issue contains a collection of 6 articles selected from high-quality submissions. The first paper of Ireneusz Czarnowski entitled "Distributed Learning with Data Reduction" consists of 120 pages and has a monograph character. The second part consists of five regular papers addressing advances in the foundations and applications of computational collective intelligence.