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Collective intelligence is still very much about human intelligence (at least for now). Its when lot of folks collaborate together and share their experiences, deductions etc. Generally everyone benefits individually and thats their motivation to participate, and generally the sum is greater than the parts. Web provide an excellent platform for this to happen.
I suppose in far future you could have AI devices collaborating together sharing their experiences and learning from each other, getting better as well.
Gagan (/^_^\) SCJP2 SCWCD IBM486 <br />Die-hard JavaMonk -- little Java a day, keeps you going.<br /><a href="http://www.objectfirst.com/blog" target="_blank" rel="nofollow">My Blog</a>
Hi Satna, Generally speaking, Collective Intelligence is a way of making decisions through considering other persons opinions. Do you think that way of working decreases our human thinking capabilies ?
To answer your question on how is Collective Intelligence and Artificial Intelligence related, I am going to quote a couple of sections from my book.
Collective intelligence is about making your application more valuable by tapping into �Wise crowds�. More formally, Collective Intelligence (CI) as used in this book simply and concisely means,
�To effectively use the information provided by others to improve one�s application�.
This is a fairly broad definition of collective intelligence � one which makes use of all types of information, both inside and outside the application � to improve the application for a user. This book introduces you to concepts from the areas of machine learning, information retrieval, and data mining and demonstrates how you can add intelligence to your application. You will be exposed to how your application can learn about individual users by using their interactions and correlate their interactions with those of others to offer a highly personalized experience.
Let�s expand on our earlier definition of collective intelligence.
Collective intelligence of users in essence is the intelligence that is extracted out from the collective set of interactions and contributions made by your users. the use of this intelligence to act as a filter for what is valuable in your application for a user. This filter takes into account a user�s preferences and interactions to provide relevant information to the user.
This filter could be the simple influence that collective user information has on a user � perhaps a rating or a review written about a product as shown in Figure 1.1 or it maybe more involved � building models to recommend personalized content to a user. This book is focused towards building the more involved models to personalize your application.
Data mining is the automated process of analyzing data to discover patterns and build predictive models. Data mining has a strong theoretical foundation and draws from many fields including mathematics, statistics, and machine learning. Machine learning is a part of artificial intelligence that deals with the development of algorithms that can be used by machines to learn the patterns in data in an automated manner. Data mining is different from data analysis, which typically deals with fitting data to already known models.
In short, Collective intelligence builds on techniques from the areas of artificial intelligence and information retrieval.