We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
We present in this paper a combination of Machine Learning based Information Retrieval (IR) techniques and stochastic language modelling in a hierarchical system that extracts sur...
Abstract. This paper explores the possibility of using a modified Expectation-Maximization algorithm to estimate parameters for a simple hierarchical generative model for XML retr...
Social annotation has gained increasing popularity in many Web-based applications, leading to an emerging research area in text analysis and information retrieval. This paper is c...
This paper presents the results of the State University of New York at Buffalo (UB) in the Mono-lingual and Multi-lingual tasks at CLEF 2004. For these tasks we used an approach ba...