By Satnam Alag
There's loads of knowledge in a crowd, yet how do you hearken to 1000 humans conversing right away? determining the wishes, wishes, and data of net clients should be like hearing a mob.
within the net 2.0 period, leveraging the collective strength of consumer contributions, interactions, and suggestions is the major to marketplace dominance. a brand new class of robust programming ideas enables you to realize the styles, inter-relationships, and person profiles-the collective intelligence--locked within the information humans go away at the back of as they surf web pages, put up blogs, and engage with different clients.
Collective Intelligence in motion is a hands-on guidebook for enforcing collective intelligence options utilizing Java. it's the first Java-based publication to stress the underlying algorithms and technical implementation of significant information accumulating and mining thoughts like studying tendencies, researching relationships, and making predictions. It presents a realistic method of personalization via combining content-based research with collaborative ways.
This booklet is for Java builders imposing Collective Intelligence in actual, high-use purposes. Following a working instance during which you harvest and use details from blogs, you discover ways to boost software program so you might embed on your personal purposes. 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 utilizing laptop studying algorithms utilizing WEKA and the Java info Mining (JDM) standard.
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Extra resources for Collective Intelligence in Action
Us shows popular tags at the site. us, a popular bookmarking site. In a tag cloud, tags are displayed alphabetically, with the size of the font representing the frequency of occurrence. The larger the font of the tag, the more frequently it occurs. VOTING Voting is another way to involve and obtain useful information from the user. Digg, a web site that allows users to contribute and vote on interesting articles, leverages this idea. Every article on Digg is submitted and voted on by the Digg community.
Think about metadata as a set of attributes that help qualify an item. When an item is a user, in most applications there’s no content associated with a user (unless Metadata your application has a text-based descriptive profile of the user). In this case, metadata for a user will consist of profile-based data and user-action based Attribute Content User-Action Based Based Based data. 5 The three sources for is also an item). We look at these three sources next. generating metadata about an item ATTRIBUTE-BASED Metadata can be generated by looking at the attributes of the user or the item.
3 4 CHAPTER 1 Understanding collective intelligence Web users are undergoing a transformation. Users are expressing themselves. This expression may be in the form of sharing their opinions on a product or a service through reviews or comments; through sharing and tagging content; through participation in an online community; or by contributing new content. This increased user interaction and participation gives rise to data that can be converted into intelligence in your application. The use of collective intelligence to personalize a site for a user, to aid him in searching and making decisions, and to make the application more sticky are cherished goals that web applications try to fulfill.