In this paper we present a system which uses ontological resources and a gene name variation generation tool to expand concepts in the original query. The novelty of our approach ...
Nicola Stokes, Yi Li, Lawrence Cavedon, Eric Huang...
Today, valuable business information is increasingly stored as unstructured data (documents, emails, etc.). For example, documents exchanged between business partners capture info...
The integration of facts derived from information extraction systems into existing knowledge bases requires a system to disambiguate entity mentions in the text. This is challengi...
Mark Dredze, Paul McNamee, Delip Rao, Adam Gerber,...
This paper describes the participation of MIRACLE research consortium at the Query Parsing task of GeoCLEF 2007. Our system is composed of three main modules. First, the Named Geo...
Due to the lack of annotated data sets, there are few studies on machine learning based approaches to extract named entities (NEs) in clinical text. The 2009 i2b2 NLP challenge is...