We present a new method for information retrieval using hidden Markov models HMMs and relate our experience with this system on the TREC-7 ad hoc task. We develop a general framew...
tion Abstract ChengXiang Zhai (Advisor: John Lafferty) Language Technologies Institute School of Computer Science Carnegie Mellon University With the dramatic increase in online in...
We investigates language models for informational and navigational web search. Retrieval on the web is a task that differs substantially from ordinary ad hoc retrieval. We perfor...
Capitalizing on the intuitive underlying assumptions of Language Modelling for Ad-Hoc Retrieval we present a novel approach that is capable of injecting the user’s context of th...
Leif Azzopardi, Mark Girolami, Cornelis Joost van ...
A well-known challenge of information retrieval is how to infer a user's underlying information need when the input query consists of only a few keywords. Question Answering (...