Collective intelligence in action / by Satnam Alag. Bookmark: au/version/; Physical Description. xxv, p.: ill. ; 24 cm. Published. 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. As Satnam Alag writes in this book, collective intelligence as a research field actually pre- dates the web. But it was after the dot-com era had.
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Part 1 Gathering data for intelligence
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Return to Book Page. Collective Intelligence in Action by Satnam Alag. 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. A new category of powerful programming techni There’s a great deal of wisdom in a crowd, but how do ocllective listen to a thousand people talking at once? A new category of powerful programming techniques lets you discover the patterns, inter-relationships, and individual profiles-the collective intelligence–locked in the data intelkigence 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. Also available is all code from the book. Paperbackpages. Published November 4th by Manning Publications first published August 15th To see what your friends thought of intelliegnce book, please sign up. To ask other readers questions about Collective Intelligence in Actionplease sign up. Be the first to ask a question about Actino Intelligence in Action.
Lists with This Book. This book is not yet featured on Listopia. Nov 12, Sopan Shewale rated it it was amazing Recommends collecitve for: Have you ever surprised to see line similar to “Hello, greatguy. We have recommendations for you” at the top when you actoin into the Amazon. Yes, this kind of functionality is very easy to implement into your application after reading Satnam’s “Collective Intelligence in Action” Have you ever wonder how Netflix is able to recommend movies, what are the latest trends in the making search more intelligent or how you can intelligently gather new content and present it to your application?
I Have you ever surprised to see line similar to “Hello, greatguy. In this book, Santnam does an excellent job providing the answers to all these questions The book covers the wide breadth of the topics with amazing focus and detail-architecture for adding intelligence, tagging and tag clouds, content aggregation through focused web crawling and from the blogospare, leveraging machine learning techniques such as clustering and predictive modeling, intelligent search and building recommendation engine.
I particularly like the approach to explain the mathematical concepts with simple examples, followed by implementing it in simple Java and then leveraging open-source software. This book can be useful if you are interested in integrating different Open Source Software to deliver Enterprise Class Application. I also liked the authors style of providing summary at the end of each chapter. He also provides huge set of very useful resources for reading further on the topics covered into the chapters.
Collective Intelligence in Action – Satnam Alag – Google Books
You must pickup this book if you are . I highly recommend it. May 21, Glenn rated it really liked it. Collective Intelligence is a big topic so the title of this book is jntelligence ambitious. The author is too. He sets out to explain all things collective intelligence circa Like any good text book, the material is presented in an iterative and incremental way. High level concepts are introduced first.
Popular features such as tag clouds and recommendation engines are defined. How collective intelligence manifests in the GUI untelligence screen flow of various popular web properties is illustrated.
Various Collective Intelligence is a big topic so the title of this book is very ambitious. Various data structures and algorithms are classified. Simple examples of some of the underlying math is worked out. Open source libraries are recommended and coding examples presented.
Topics are introduced simply at first and revisited in later chapters satjam ever increasing amounts of detail. However, there’s a lot of math in the topic of collective intelligence and this is not a colkective book. Neither does it take a “heads up” or “for dummies” approach. Instead, it aims somewhere in the middle which gives the book a bit of an identity crisis. If you’re a script jock or a web master whose level of technical competence doesn’t extend too far past embedding a youtube video or paypal “buy now” button on your pages, then the most that you are going to get out of this book is just the high level introductory material.
The formally trained software engineer can treat this book as a great introductory survey level course on the subject that does attempt to peal back some of the layers of complexity. It is neither definitive nor canonical so you will be doing more research and studying before you deploy any sophisticated collective intelligence in your applications. Aug 06, Phoenix rated it really liked it Shelves: The basic idea is that one can catalog lntelligence by removing irrelevant intellibence adjectives, abstract pronouns, conjunctives and “stemming” the remaining words ie: One simple result is the actioon to produce “word clouds”.
Similarity between documents is measured by taking the dot product of the two vectors. Any document compared to itself would have a dot product of 1. Two documents with no common actiin words would have a dot product of zero. Similar docs would have a high value close to 1, say.
Dissimilar docs would have a low coefficient, say. Even mistaking “sewer” a conduit for waste and sewer one who uses a needle and col,ective is taken into account because both docs would only be similar on a actoin of keywords, and alg on most others. What’s really neat is how this information gets collected and can be applied.
Social networking sites, including the one you are reading right now, Amazon. Browse for a book while logged on then that’s something you are interested in. Approve a review the words in the collectivee, summary of the book and the title counts towards your interests.
Disapprove and that counts against your interests. Write a review and the words you write become part of your cumulative profile as well, reduced to a vector or vectors of keywords and frequencies. Here’s how it gets actikn One of Amazon’s marketing tools is it’s “recommendation engine”. The book talks about Netflix recommendation engine and business model. The more Amazon caters to what you are interested in, and doesn’t bother you with irrelevancies, the happier you may be.
Other applications discussed include the automatic creation of folksonomies taxonomies based on popular usage using cluster analysis and categorization using Bayes theorem. In addition to recommendation engines Alag points out the usefulness of these techniques to Search and points out several search engines that apply this approach as does Googletools that search out and provide news based on your preferences, or suggest “friends” ie: Facebook or eHarmony might use these ideassearch for similar material to identify copyright infringement, email filters that keep out spam for rolex watches or viagra unless you are interested in rolex watches or viagraconstruct a virus detection engine based on code phrases or early detection of epidemics or adverse reactions to medication through similarities in medical reports.
Alag himself appears to be working at a biotech firm NextBio that matches public medical and genome related data to data held by private companies. Some of the basic tools discussed are Lucene, a free version of what Google will sell you for a search engine, Nutch, a free web crawler, both of which require coding and WEKA, a free open source data mining package that looks usable by the rest of us. Loved the book and the author’s organization of the material.
Intelpigence of the social implications are intellibence, especially for privacy concerns, but so is intellligence implication of not leveraging the information that one holds within your organization to provide the best possible service.
For example the World Bank has the capability not necessarily using these methods to match similar collectivf around the world so that experience gained in one area can be found and applied elsewhere. This is a key fast moving tech that one needs to understand in order to see where we are going as a society. The book also recommends and has sparked my interest in the site [ Finally a note to SF fans, this may be the point at which the Web starts to appear to be intelligent.
Collective Intelligence : Satnam Alag :
Feb 02, AHolly rated it really liked it. I have just started this book butcan already tell that it contains far more useful information than o’reilly’s. Oreilly’s seemed a little too, “type this Petro rated it did not like it Jun 04, Duoyi Wu rated it really liked it Mar 16, Benjamin Anderson rated it liked it Dec 18, Budi Susanto rated it really liked it Apr 03, David Boyle rated it it was amazing Jul 07, Gier rated it collectuve liked it Feb 12, Will Godfrey rated it really liked it Oct 13, Chet rated it liked it Nov 17,