We propose a novel probabilistic method based on the Hidden Markov Model (HMM) to learn the structure of a Latent Variable Model (LVM) for query language modeling. In the proposed...
Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. While topic models can p...
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyv...
In this paper we introduce POLAR, a probabilistic objectoriented logical framework for annotation-based information retrieval. In POLAR, the knowledge about digital objects, annot...
This paper presents a Japanese information retrieval method using the dependency relationship between words and semantic and statistical information about them. Our method gives a...
– With the World Wide Web popularity the information retrieval area has a new challenge intending to retrieve information resources by their meaning by using a knowledge base. No...