There's a great deal of wisdom in a crowd, but how do you listen to a thousand people talking at once? Identifying the wants, needs, and knowledge of internet users can be like listening to a mob. In the Web 2.0 era, leveraging the collective power of user contributions, interactions, and feedback is the key to market dominance. A new category of powerful programming techniques lets you discover the patterns, inter-relationships, and individual profiles-the collective intelligence--locked in the data people leave behind as they surf websites, post blogs, and interact with other users. Collective Intelligence in Action is a hands-on guidebook for implementing collective intelligence concepts using Java. It is the first Java-based book to emphasize the underlying algorithms and technical implementation of vital data gathering and mining techniques like analyzing trends, discovering relationships, and making predictions. It provides a pragmatic approach to personalization by combining content-based analysis with collaborative approaches. This book is for Java developers implementing Collective Intelligence in real, high-use applications. Following a running example in which you harvest and use information from blogs, you learn to develop software that you can embed in your own applications. The code examples are immediately reusable and give the Java developer a working collective intelligence toolkit. Along the way, you work with, a number of APIs and open-source toolkits including text analysis and search using Lucene, web-crawling using Nutch, and applying machine learning algorithms using WEKA and the Java Data Mining (JDM) standard. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

Taking as its central argument the question of whether an intelligence system is both desirable and feasible within the UN structure, this study explores the complex and sometimes, irreconcilable issues of strategic intelligence in a sharing context. This study further identifies and develops both conceptual and empirical framework for a viable intelligence capability in multi-agency institutions; exploring and suggesting, for the first time, necessary and acceptable conditions for collective intelligence in an environment characterised by conflicting objectives among international actors. It takes as its main premise the view that the United Nations and the world of intelligence are two separate and contradicting entities that conflict in both principles and operating doctrines. From this point of view, the author explores the many theoretical imperatives which set the two institutions apart and stand in the way of understanding the concepts. He also goes further to examine the contexts in which the contradictions could be harmonised. This book is one of a handful of studies; it is highly original in that it focuses on the relationship between intelligence and the United Nations. While previous efforts to examine the subject have approached it from a strictly practical point of view, this work is clearly focused on the linkages between theory and practice. The methodology is thoughtful and broad in scope, and the work is theoretically well informed and sophisticated in its analysis of the subject matter. The discussion of aspects of the theory of international relations--specifically those relevant to the role of international governance and the examination of the working of the UN--and several case studies of the UN in action are further characteristics of the rigor and clarity in which the author approaches the study in an intelligent and illuminating manner. While the book's many contributions can be found at various levels of originality, its thorough assessment of the linkage between theory and policy stands out, perhaps, as the most important and primary contribution to the areas of collective intelligence and international relations. Other important contributions include the case study analyses and specification of criteria for evaluating collective security intelligence mechanisms. In essence, a lack of scholarly efforts to ground the notion of collective intelligence within a rigorous intellectual framework is a significant vacuum in the study of intelligence which the present study has filled. Scholars working within the international relations discipline and more specifically issues of global governance and security will find this study invaluable. The book should also appeal to many categories of readers working in information and policy environment, as well as governmental and non-governmental organisations.

Experts describe the latest research in a rapidly growing multidisciplinary field, the study of groups of individuals acting collectively in ways that seem intelligent. Intelligence does not arise only in individual brains; it also arises in groups of individuals. This is collective intelligence: groups of individuals acting collectively in ways that seem intelligent. In recent years, a new kind of collective intelligence has emerged: interconnected groups of people and computers, collectively doing intelligent things. Today these groups are engaged in tasks that range from writing software to predicting the results of presidential elections. This volume reports on the latest research in the study of collective intelligence, laying out a shared set of research challenges from a variety of disciplinary and methodological perspectives. Taken together, these essays—by leading researchers from such fields as computer science, biology, economics, and psychology—lay the foundation for a new multidisciplinary field. Each essay describes the work on collective intelligence in a particular discipline—for example, economics and the study of markets; biology and research on emergent behavior in ant colonies; human-computer interaction and artificial intelligence; and cognitive psychology and the “wisdom of crowds” effect. Other areas in social science covered include social psychology, organizational theory, law, and communications. Contributors Eytan Adar, Ishani Aggarwal, Yochai Benkler, Michael S. Bernstein, Jeffrey P. Bigham, Jonathan Bragg, Deborah M. Gordon, Benjamin Mako Hill, Christopher H. Lin, Andrew W. Lo, Thomas W. Malone, Mausam, Brent Miller, Aaron Shaw, Mark Steyvers, Daniel S. Weld, Anita Williams Woolley

The five volume set CCIS 224-228 constitutes the refereed proceedings of the International conference on Applied Informatics and Communication, ICAIC 2011, held in Xi'an, China in August 2011. The 446 revised papers presented were carefully reviewed and selected from numerous submissions. The papers cover a broad range of topics in computer science and interdisciplinary applications including control, hardware and software systems, neural computing, wireless networks, information systems, and image processing.

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

The book focuses on Social Collective Intelligence, a term used to denote a class of socio-technical systems that combine, in a coordinated way, the strengths of humans, machines and collectives in terms of competences, knowledge and problem solving capabilities with the communication, computing and storage capabilities of advanced ICT. Social Collective Intelligence opens a number of challenges for researchers in both computer science and social sciences; at the same time it provides an innovative approach to solve challenges in diverse application domains, ranging from health to education and organization of work. The book will provide a cohesive and holistic treatment of Social Collective Intelligence, including challenges emerging in various disciplines (computer science, sociology, ethics) and opportunities for innovating in various application areas. By going through the book the reader will gauge insight and knowledge into the challenges and opportunities provided by this new, exciting, field of investigation. Benefits for scientists will be in terms of accessing a comprehensive treatment of the open research challenges in a multidisciplinary perspective. Benefits for practitioners and applied researchers will be in terms of access to novel approaches to tackle relevant problems in their field. Benefits for policy-makers and public bodies representatives will be in terms of understanding how technological advances can support them in supporting the progress of society and economy.

"A new field of collective intelligence has emerged in the last few years, prompted by a wave of digital technologies that make it possible for organizations and societies to think at large scale. This "bigger mind"--human and machine capabilities working together--has the potential to solve the great challenges of our time. So why do smart technologies not automatically lead to smart results? Gathering insights from diverse fields, including philosophy, computer science, and biology, Big Mind reveals how collective intelligence can guide corporations, governments, universities, and societies to make the most of human brains and digital technologies"--Amazon.com.

Deeper City is the first major application of new thinking on ‘deeper complexity’, applied to grand challenges such as runaway urbanization, climate change and rising inequality. The author provides a new framework for the collective intelligence – the capacity for learning and synergy – in many-layered cities, technologies, economies, ecologies and political systems. The key is in synergistic mapping and design, which can move beyond smart ‘winner-takes-all’ competition, towards wiser human systems of cooperation where ‘winners-are-all’. Forty distinct pathways ‘from smart to wise’ are mapped in Deeper City and presented for strategic action, ranging from local neighbourhoods to global finance. As an atlas of the future, and resource library of pathway mappings, this book expands on the author’s previous work, City-Region 2020. From a decade of development and testing, Deeper City combines visual thinking with a narrative style and practical guidance. This book will be indispensable for those seeking a sustainable future – students, politicians, planners, systems designers, activists, engineers and researchers. A new postscript looks at how these methods can work with respect to the 2020 pandemic, and asks, ‘How can we turn crisis towards transformation?'

This book is a selection of results obtained within three years of research performed under SYNAT—a nation-wide scientific project aiming at creating an infrastructure for scientific content storage and sharing for academia, education and open knowledge society in Poland. The book is intended to be the last of the series related to the SYNAT project. The previous books, titled “Intelligent Tools for Building a Scientific Information Platform” and “Intelligent Tools for Building a Scientific Information Platform: Advanced Architectures and Solutions”, were published as volumes 390 and 467 in Springer's Studies in Computational Intelligence. Its contents is based on the SYNAT 2013 Workshop held in Warsaw. The papers included in this volume present an overview and insight into information retrieval, repository systems, text processing, ontology-based systems, text mining, multimedia data processing and advanced software engineering, addressing the problems of implementing intelligent tools for building a scientific information platform.