Supporting situated actions in high volume conversational data situations
Christopher Lueg · 1998
The global conferencing system Usenet nears offers an amount of articles per day that exceeds human cognitive capabilities by far although the articles are already organized in hierarchically structured discussion groups covering distinct topics.We report here on a situated information filtering system that significantly reduces the burden by supporting the user in acting situated.Interpreting the user's actions as situated actions, the approach complements current filtering and recommender approaches by completely avoiding the modeling of user interests; the user is the only instance for assigning (un-)interestingness to Usenet discussions.