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Knowledge Acquisition from Text
Dekang Lin
Text is arguably the richest repository of human knowledge. Two
approaches have commonly been adopted in knowledge acquisition from
text. One is to define specific patterns and extract instances
matching these patterns in a text collection. This has been used to
find relationships between words, such as is-a and part-whole. Another
approach is based on indirect associations between words in text, as
exemplified by many methods for computing word similarity. I will
present extension and generalization of the previous methods and show
that seemingly deep linguistic or world knowledge may be acquired with
superficial statistics.
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Dernière mise à jour : Wed Oct 22 11:21:03 2008
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