A probabilistic learning model for vague queries and missing or imprecise information in databases is described. Instead of retrieving only a set of answers, our approach yields a...
In this report, we unify two quite distinct approaches to information retrieval: region models and language models. Region models were developed for structured document retrieval....
In a sequential Bayesian ranking and selection problem with independent normal populations and common known variance, we study a previously introduced measurement policy which we ...
Web is the boundless source of information and no one is able to process the vast amount of new documents published on the web every day, even with filtering out the documents the ...
We derive a knowledge gradient policy for an optimal learning problem on a graph, in which we use sequential measurements to refine Bayesian estimates of individual edge values i...