CBB seminar by W. John Wilbur

Bldg. 38A, B2 library, 11 am, Tuesday, April 1, 2008

 

Title: Random Background Learning: A new approach to unsupervised machine learning as applied to the morpho-semantic relation in MEDLINE.

 

Abstract:  Morphological analysis as applied to English has generally involved the study of rules for inflections and derivations. 
Recent work has attempted to derive such rules from automatic analysis of corpora. Here we study similar issues, but in the context 
of the biological literature. We introduce a new approach which allows us to assign probabilities of the semantic relatedness
 of pairs of tokens that occur in text in consequence of their relatedness as character strings. Our analysis is based on over
 84 million sentences that compose the MEDLINE database, over 2.3 million token types that occur in MEDLINE, and enables us to 
identify over 36 million token type pairs which have assigned probabilities of semantic relatedness of at least 0.7 based on 
their similarity as strings.