Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Summarizing local context to personalize global web search
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Approaches to Context-Based Knowledge Share and Reuse
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01
A live-user evaluation of collaborative web search
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
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The task of knowledge-gathering through an Information System has become increasingly challenging, due to the multitude of activities that are being facilitated through the system. A user-centric approach is presented in this paper where various activities executed by a user, for a knowledge-gathering task, are mapped to certain cognitive states in our model and the transitions between those states are used to indicate the progress made by the user. We propose a socio-contextual filtering algorithm for discovering similar tasks that were executed by other users and claim that such a socio-contextually related task would help in reducing the cognitive load, efforts and the time required for a user, naïve to a given knowledge gathering task. We demonstrate this through the fewer number of state transitions that occur in our model for a guided user.