The research paper Collective Intelligence Computer Science Engineering Seminar Topics explains in detail what collective intelligence is Collective intelligence is defined as the ability of a group to solve more problems than its individual members. The research paper posits that that the obstacles created by individual cognitive limits and the difficulty of coordination can be overcome by using a collective mental map (CMM). A CMM is defined as an external memory with shared read/write access that represents problem states, actions and preferences for actions.
According to collective intelligence A system is more intelligent than another system if in a given time interval it can solve more problems, or find better solutions to the same problems. A group can then be said to exhibit collective intelligence if it can find more or better solutions than the whole of all solutions that would be found by its members working individually.
Examples of Collective Intelligence: The research abstract quotes pertinent examples pertaining to Collective Intelligence. It says that all organizations, whether they are firms, institutions or sporting teams, are created on the assumption that their members can do more together than they could do alone.
Collective Mental Maps: The research abstract casts light on Collective Mental Maps. It says that a collective mental map functions first of all as a shared memory. Various discoveries by members of the collective are registered and stored in this memory, so that the information will remain available for as long as necessary.
Benefits of CMM: The paper suggests some obvious benefits of CMM. Instead of being limited to the few links present in the document being consulted, a user would be able to choose from an extensive, but intelligently selected list of related documents, ordered by the probability that they would be relevant. The paper also quotes examples saying that such a list of suggested links has already been implemented by the Alexa Corporation and incorporated in the Netscape and Internet Explorer browsers.
Conclusion:
The research paper concludes on a note describing CMM and calling it a “global brain”. Although the first commercial applications of some of these techniques are already appearing, it is clear that still a lot of research needs to be done before it can be certain that the proposed algorithms are ready for the task. There are many possible variations on the methods discussed, and there are many other sources of collective knowledge to be mined. The best-combined method will likely be found by testing out a variety of approaches in a variety of circumstances.
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