Abstract
This chapter presents an approach to acquiring knowledge from an on-line corpus of text automatically, based on the use of mutual information statistics. More specifically, it explores the potential for automatically constructing a two-tier model of semantic memory from on-line textual corpora as follows:
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Automatically construct the interrelationships between concepts in semantic memory (i.e., construct the relational tier of semantic memory).
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Automatically encode the background frame knowledge associated with the concepts in semantic memory (i.e., encode each concept’s associational knowledge).
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Dynamically change semantic memory as new texts are processed (i.e., evolve semantic memory in response to new input).
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© 1994 Springer Science+Business Media New York
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Bookman, L.A. (1994). Experiments in Acquiring Knowledge from On-line Corpora. In: Trajectories through Knowledge Space. The Springer International Series in Engineering and Computer Science, vol 286. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2780-0_7
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DOI: https://doi.org/10.1007/978-1-4615-2780-0_7
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-6201-2
Online ISBN: 978-1-4615-2780-0
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