Analogy in the large

Authors:
Kenneth B. Haase
Affiliations:
MIT Media Laboratory, Cambridge, Massachusetts
Venue:
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Year:
1995

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Abstract

This article discusses the use of analogy to index and organize large databases of information We describe the design and implementation of an analogical database supporting tens to hundreds of thousands of cases The contents of the database are parsed news articles represented as networks of grammatical relations with references into WordNet for word meaning information The virtue of this approach is its domain independent handling of content analysis Efficient algorithms for indexing and matching in this database are described and briefly discussed and examples of their performance are discussed.