Traditional documentation for computer-based procedures is difficult to use: readers have trouble navigating long complex instructions, have trouble mapping from the text to displ...
Lawrence D. Bergman, Vittorio Castelli, Tessa A. L...
This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling ...
In this paper we study the problem of collecting training samples for building enterprise taxonomies. We develop a computer-aided tool named InfoAnalyzer, which can effectively as...
Techniques for learning from data typically require data to be in standard form. Measurements must be encoded in a numerical format such as binary true-or-false features, numerica...
V. Seshadri, Raguram Sasisekharan, Sholom M. Weiss
This work addresses the use of computational linguistic analysis techniques for conceptual graphs learning from unstructured texts. A technique including both content mining and i...