We explore a new Bayesian model for probabilistic grammars, a family of distributions over discrete structures that includes hidden Markov models and probabilistic context-free gr...
A common task in many applications is to find persons who are knowledgeable about a given topic (i.e., expert finding). In this paper, we propose and develop a general probabilis...
The approach of using passage-level evidence for document retrieval has shown mixed results when it is applied to a variety of test beds with different characteristics. One main r...
In this study, we describe our system at the Intellectual Property track of the 2009 CrossLanguage Evaluation Forum campaign (CLEF-IP). The CLEF-IP track addressed prior art searc...
We show how Recursive Markov Chains (RMCs) and their restrictions can define probabilistic distributions over XML documents, and study tractability of querying over such models. ...
Michael Benedikt, Evgeny Kharlamov, Dan Olteanu, P...