A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is dened as the maximum a posteriori (MAP) probability estimate...
A novel random text generation model is introduced. Unlike in previous random text models, that mainly aim at producing a Zipfian distribution of word frequencies, our model also ...
Abstract. Ontologies are today used to annotate web data with machine processable semantics and for domain modeling. As the use of ontologies increases and the ontologies themselve...
A growing number of applications are built on top of search engines and issue complex structured queries. This paper contributes a customisable ranking-based processing of such qu...
We consider the task of suggesting related queries to users after they issue their initial query to a web search engine. We propose a machine learning approach to learn the probab...