August 17, 2005
Generic Soft Pattern Models for Definitional QA
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Discussions on Both Models
•Capture the same information
–The importance of a token’s position in the context of the search term
–The sequential order of tokens
•Different in complexity
–Bigram model
•Simplified Markov model with each token as a state
•Captures token sequential information by bigram probabilities
–PHMM model
•More complex – aggregated token sequential information by hidden state transition probabilities
•Experimental results show
–PHMM is less sensitive to model length
–PHMM may benefit more by using more training data