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Collective Intelligence and its Implementation on the Web: Algorithms to Develop a Collective Mental Map

Francis Heylighen (fheyligh@vub.ac.be)
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Francis Heylighen: Free University of Brussels

Computational and Mathematical Organization Theory, 1999, vol. 5, issue 3, No 4, 253-280

Abstract: Abstract Collective intelligence is defined as the ability of a group to solve more problems than its individual members. It is argued 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. It can be formalized as a weighted, directed graph. The creation of a network of pheromone trails by ant colonies points us to some basic mechanisms of CMM development: averaging of individual preferences, amplification of weak links by positive feedback, and integration of specialised subnetworks through division of labor. Similar mechanisms can be used to transform the World-Wide Web into a CMM, by supplementing it with weighted links. Two types of algorithms are explored: 1) the co-occurrence of links in web pages or user selections can be used to compute a matrix of link strengths, thus generalizing the technique of &201C;collaborative filtering&201D;; 2) learning web rules extract information from a user&2018;s sequential path through the web in order to change link strengths and create new links. The resulting weighted web can be used to facilitate problem-solving by suggesting related links to the user, or, more powerfully, by supporting a software agent that discovers relevant documents through spreading activation.

Keywords: collective intelligence; world-wide web; collaborative filtering; mental maps; problem-solving; preference functions; external memory; division of labor (search for similar items in EconPapers)
Date: 1999
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Citations: View citations in EconPapers (11)

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DOI: 10.1023/A:1009690407292

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