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Complex question answering: homogeneous or heterogeneous, which ensemble is better?

Chali, Yllias and Sadid, Hassan and Mojahid, Mustapha Complex question answering: homogeneous or heterogeneous, which ensemble is better? (2014) In: 19th International Conference on Application of Natural Language to Information Systems (NLDB 2014), 18 June 2014 - 20 June 2014 (Montpellier, France).

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Official URL: http://dx.doi.org/10.1007/978-3-319-07983-7_21

Abstract

This paper applies homogeneous and heterogeneous ensembles to perform the complex question answering task. For the homogeneous ensemble, we employ Support Vector Machines (SVM) as the learning algorithm and use a Cross-Validation Committees (CVC) approach to form several base models. We use SVM, Hidden Markov Models (HMM), Conditional Random Fields (CRF), and Maximum Entropy (MaxEnt) techniques to build different base models for the heterogeneous ensemble. Experimental analyses demonstrate that both ensemble methods outperform conventional systems and heterogeneous ensemble is better.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to Springer editor. This papers appears in Volume 8455 of Lecture Notes in Computer Science. ISBN 978-3-319-07982-0. The original PDF is available at: http://link.springer.com/chapter/10.1007%2F978-3-319-07983-7_21
HAL Id:hal-01402563
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Philips Research (USA)
Other partners > University of Lethbridge (CANADA)
Laboratory name:
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Deposited By: IRIT IRIT
Deposited On:16 Nov 2016 08:01

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