Supporting cooperative and personal surfing with a desktop assistant
Proceedings of the 10th annual ACM symposium on User interface software and technology
Using information scent to model user information needs and actions and the Web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Web search engine working as a bee hive
Web Intelligence and Agent Systems
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As the amount of Web content grows and diversifies, traditional organizational structures such as keyword search engines and static directories become less useful and comprehensive, requiring more user effort to find relevant information. Information foraging theory [4] and collaborative filtering [6] address this problem in different but compatible ways. This paper introduces an approach called collaborative foraging that applies the biological metaphors of information foraging to the cooperative filtering. The approach assumes that humans best pursue relevent Web content according to optimal foraging behavior, collaborating with communities of like-minded foragers. This paper gives preliminary results of a limited implementation.