Collective Intelligence in Action

Collective Intelligence in Action

Author: Satnam Alag

Publisher: Simon and Schuster

Published: 2008-09-30

Total Pages: 609

ISBN-13: 163835538X

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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.


Big Mind

Big Mind

Author: Geoff Mulgan

Publisher: Princeton University Press

Published: 2019-11-12

Total Pages: 288

ISBN-13: 0691196168

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"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.


Programming Collective Intelligence

Programming Collective Intelligence

Author: Toby Segaran

Publisher: "O'Reilly Media, Inc."

Published: 2007-08-16

Total Pages: 361

ISBN-13: 0596550685

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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


Artificial Intelligence for Knowledge Management

Artificial Intelligence for Knowledge Management

Author: Eunika Mercier-Laurent

Publisher: Springer

Published: 2014-05-23

Total Pages: 199

ISBN-13: 3642548970

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This book features a selection of papers presented at the First IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2012, held in Montpellier, France, in August 2012, in conjunction with the 20th European Conference on Artificial Intelligence, ECAI 2012. The 11 revised and extended papers were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management.


Knowledge Management Strategies: A Handbook of Applied Technologies

Knowledge Management Strategies: A Handbook of Applied Technologies

Author: Lytras, Miltiadis D.

Publisher: IGI Global

Published: 2008-04-30

Total Pages: 390

ISBN-13: 1599046059

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We recognize knowledge management as a socio-technical phenomenon where the basic social constructs such as person, team, and organization require support from information communication technology applications. In an era of business transition, the effective management of knowledge is proposed as a strategy that effectively utilizes organizational intangible assets. Knowledge Management Strategies: A Handbook of Applied Technologies provides practical guidelines for the implementation of knowledge management strategies through the discussion of specific technologies and taxonomies of knowledge management applications. A critical mass of some of the most sought-after research of our information technology and business world, this book proves an essential addition to every reference library collection.


Advances in Computational Collective Intelligence

Advances in Computational Collective Intelligence

Author: Krystian Wojtkiewicz

Publisher: Springer Nature

Published: 2021-09-29

Total Pages: 742

ISBN-13: 303088113X

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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.


Knowledge Management in the Intelligence Enterprise

Knowledge Management in the Intelligence Enterprise

Author: Edward Waltz

Publisher: Artech House

Published: 2003

Total Pages: 374

ISBN-13: 1580534945

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If you are responsible for the management of an intelligence enterprise operation and its timely and accurate delivery of reliable intelligence to key decision-makers, this book is must reading. It is the first easy-to-understand, system-level book that specifically applies knowledge management principles, practices and technologies to the intelligence domain. The book describes the essential principles of intelligence, from collection, processing and analysis, to dissemination for both national intelligence and business applications.


ECKM2014-Proceedings of the 15th European conference on Knowledge Management

ECKM2014-Proceedings of the 15th European conference on Knowledge Management

Author: Carla Vivas

Publisher: Academic Conferences and Publishing International

Published: 2014-10-01

Total Pages: 474

ISBN-13: 1910309346

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The world economy in which we are living poses challenges that lead to a realization that 'more of the same' will be difficult to sustain. This provides an illustration that, in order to create new or modified knowledge practices, strengthen customer relationships and thus positively influence customer satisfaction, organizations must be flexible in configuring (combining) knowledge and knowledge structures in a way that is appropriate for delivering value to the customer. It must simultaneously develop effective strategies for updating the knowledge of its staff members necessary for underpinning the creation and delivery of appropriate knowledge services. Thus, unlearning (forgetting) becomes a critical means for organizational success. The ECKM community of scholars has already initiated dialogue that links its particular strengths to innovation issues. This conference aims to further that dialogue by attracting leading edge work that leverages the ECKM community's in-depth understanding of learning and unlearning to better understand knowledge management. Our aim is to stimulate breakthrough research streams linking learning, unlearning and knowledge management. How can organizations tailor, use, and extend techniques and tools from knowledge management for improving their business practices and processes? Building upon existing work on knowledge management (KM) and organizational learning, the conference will promote interdisciplinary approaches from computer science and information systems, business, management and organization science as well as cognitive science. Emphasis will be put on systematic learning from experience, KM tools and KM success factors. A special interest belongs to knowledge management initiatives which are lightweight (i.e., do not place considerable additional burden on users and KM experts), allow an incremental adoption (i.e., do not require large up-front investment before any return of investment is at least visible), and are flexible regarding frequent changes in experts and topics. Continuing the success of the ECKM conference series since 2000, the 2015 conference will provide an international communication forum bringing together academia and industry for discussing the progress made and addressing the challenges faced by continuous learning in knowledge-intensive organizations.