In this report, we describe our question-answering system SAIQA-e (System for Advanced Interactive Question Answering in English) which ran the main task of TREC-10's QA-trac...
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...
Background: The ability to distinguish between genes and proteins is essential for understanding biological text. Support Vector Machines (SVMs) have been proven to be very effici...
Tapio Pahikkala, Filip Ginter, Jorma Boberg, Jouni...
Ambiguous person names are a problem in many forms of written text, including that which is found on the Web. In this paper we explore the use of unsupervised clustering techniques...
As natural language understanding research advances towards deeper knowledge modeling, the tasks become more and more complex: we are interested in more nuanced word characteristi...
Radu Florian, Hongyan Jing, Nanda Kambhatla, Imed ...