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...
We propose a semantic tagger that provides high level concept information for phrases based on several kinds of low level information about words in clinical narrative texts. The ...
This paper presents a new approach to determine the senses of words in queries by using WordNet. In our approach, noun phrases in a query are determined first. For each word in th...
This paper presents an unsupervised learning approach to building a non-English (Arabic) stemmer. The stemming model is based on statistical machine translation and it uses an Eng...
This paper reports on work done for the Genomics Track at TREC 2004 by ConverSpeech LLC in conjunction with scientists at the Saccharomyces Genome Database (SGD), the model organi...
Colleen E. Crangle, Alex Zbyslaw, J. Michael Cherr...