Abstract
The CALO project at SRI International provides unique opportunities to explore the boundaries of knowledge representation and organization in a learning environment. A goal reported here is to develop methods for assistance in the preparation of documents through a topic map framework populated by combinations of machine learning and recorded social gestures. This work in progress continues the evolution of Tagomizer, our social bookmarking application, adding features necessary for annotations of websites beyond simple bookmark-like tagging, including the creation of new subjects in the topic map. We report on the coupling of Tagomizer with a Java wiki engine, and show how this new framework will serve as a platform for CALO’s DocAssist application.
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Park, J. (2008). Toward a Topic Maps Amanuensis. In: Maicher, L., Garshol, L.M. (eds) Scaling Topic Maps. TMRA 2007. Lecture Notes in Computer Science(), vol 4999. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70874-2_14
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DOI: https://doi.org/10.1007/978-3-540-70874-2_14
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