—We present an information retrieval model for combining evidence from concept-based semantics, term statistics, and context for improving search precision of genomics literature...
Abstract. This paper suggests a novel representation for documents that is intended to improve precision. This representation is generated by combining two central techniques: Rand...
We propose an approach for extracting relations between entities from biomedical literature based solely on shallow linguistic information. We use a combination of kernel function...
Unsupervised word representations are very useful in NLP tasks both as inputs to learning algorithms and as extra word features in NLP systems. However, most of these models are b...
Eric H. Huang, Richard Socher, Christopher D. Mann...
In this paper, we reported some experiments conducted by our members in the SIG team at the IRIT laboratory in the University of Toulouse within the context of the medical informat...