By Satnam Alag
There's loads of knowledge in a crowd, yet how do you hearken to 1000 humans conversing instantaneously? deciding on the desires, wishes, and data of web clients might be like hearing a mob.
within the internet 2.0 period, leveraging the collective strength of consumer contributions, interactions, and suggestions is the foremost to marketplace dominance. a brand new class of robust programming strategies allows you to become aware of the styles, inter-relationships, and person profiles-the collective intelligence--locked within the facts humans depart in the back of as they surf web pages, submit blogs, and have interaction with different clients.
Collective Intelligence in motion is a hands-on guidebook for imposing collective intelligence thoughts utilizing Java. it's the first Java-based booklet to stress the underlying algorithms and technical implementation of significant facts amassing and mining options like reading developments, getting to know relationships, and making predictions. It presents a practical method of personalization by means of combining content-based research with collaborative methods.
This booklet is for Java builders enforcing Collective Intelligence in genuine, high-use functions. Following a operating instance within which you harvest and use info from blogs, you discover ways to improve software program so that you can embed on your personal functions. The code examples are instantly reusable and provides the Java developer a operating collective intelligence toolkit.
alongside the best way, you're employed with, a couple of APIs and open-source toolkits together with textual content research and seek utilizing Lucene, web-crawling utilizing Nutch, and employing laptop studying algorithms utilizing WEKA and the Java facts Mining (JDM) standard.
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Extra resources for Collective Intelligence in Action
User-centric sites leverage collective intelligence to present relevant content to the user. 8 As shown in 2. Community 1. Core Competency Social Networking, Find Answers, Jobs User 3. User-Generated Content Q&A, Blogs, Tagging, Reviews 7 8 User profile, interaction history, connections 4. com) the screenshot, the LinkedIn application leverages the four components of usercentric applications: ■ ■ ■ ■ 9 Core competency — Users come to the site to connect with others and build their professional profiles.
If your application is a social-networking application, or you’re looking to connect one user with another, then a user is also a type of item. 4 A user interacts with items, which have associated metadata. Associated with each item is metadata, which may be in the form of professionally developed keywords, user-generated tags, keywords extracted by an algorithm after analyzing the text, ratings, popularity ranking, or just about anything that provides a higher level of information about the item and can be used to correlate items together.
As those others viewed this video, other related videos popped up as recommendations, keeping the user further engaged. Ultimately, many of these viewers also became submitters and uploaded their own videos as well. As the number of videos increased, the site became more and more attractive for new users to visit. org/wiki/Hundredth_Monkey As of September 2006 6 CHAPTER 1 Understanding collective intelligence Whether you’re a budding startup, a recognized market leader, or looking to take an emerging application or web site to the next level, harnessing information from users improves the perceived value of the application to both current and prospective users.
Collective Intelligence in Action by Satnam Alag