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» Using Machine Learning and Text Mining in Question Answering
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BMCBI
2005
155views more  BMCBI 2005»
14 years 9 months ago
Mining protein function from text using term-based support vector machines
Background: Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We...
Simon B. Rice, Goran Nenadic, Benjamin J. Stapley
AIIA
2009
Springer
15 years 4 months ago
Analyzing Interactive QA Dialogues Using Logistic Regression Models
With traditional Question Answering (QA) systems having reached nearly satisfactory performance, an emerging challenge is the development of successful Interactive Question Answeri...
Manuel Kirschner, Raffaella Bernardi, Marco Baroni...
LOGCOM
2008
104views more  LOGCOM 2008»
14 years 9 months ago
Testing the Reasoning for Question Answering Validation
Question Answering (QA) is a task that deserves more collaboration between Natural Language Processing (NLP) and Knowledge Representation (KR) communities, not only to introduce r...
Anselmo Peñas, Álvaro Rodrigo, Valen...
IR
2011
14 years 4 months ago
Learning to rank for why-question answering
In this paper, we evaluate a number of machine learning techniques for the task of ranking answers to why-questions. We use TF-IDF together with a set of 36 linguistically motivate...
Suzan Verberne, Hans van Halteren, Daphne Theijsse...
IR
2006
14 years 9 months ago
Table extraction for answer retrieval
The ability to find tables and extract information from them is a necessary component of many information retrieval tasks. Documents often contain tables in order to communicate d...
Xing Wei, W. Bruce Croft, Andrew McCallum