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dc.contributor.advisorDowning, Keith
dc.contributor.authorRykkelid, Håvard
dc.date.accessioned2018-11-05T15:00:26Z
dc.date.available2018-11-05T15:00:26Z
dc.date.created2006-06-02
dc.date.issued2006
dc.identifierntnudaim:1539
dc.identifier.urihttp://hdl.handle.net/11250/2571036
dc.description.abstractIn testing the viability of automatic knowledge-acquisition, using simple techniques and brute force on the Internet, a system was implemented in Java. Techniques from both multi-agent system and swarm intelligence paradigms were used to structure the system, improve searches, increase stability and increase modularity. The system presented relies on using existing search-engines to find texts on the World Wide Web, containing a user-specified key-word. Knowledge is identified in the texts using key-sentences, terms related to the key-word becomes new key-words in an incremental search. The result is expressed as sentences in a KR-language. The answers from a run were often interesting and surprising, and gave information beyond an encyclopedic scope, even if the answers often contained false information. The results of the implemented system verified the viability of both the designed framework and the theory behind it.
dc.languageeng
dc.publisherNTNU
dc.subjectInformatikk, Kunstig intelligens og læring
dc.titleSwarm-based information retrieval - Automatic knowledge-acquisition using MAS, SI and the Internet
dc.typeMaster thesis


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