Socio-contextual Filters for Discovering Similar Knowledge-Gathering Tasks in Generic Information Systems

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, naive 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.