Learning textual entailment using SVMs and string similarity measures

Proceedings of the Annual Meeting of the Association for Computational Linguistics

Volumn , Issue , 2007, Pages 42-47

  Malakasiotis, Prodromos ^a   Androutsopoulos, Ion ^a  

^a ATHENS UNIVERSITY OF ECONOMICS AND BUSINESS   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

DEEP LEARNING; NATURAL LANGUAGE PROCESSING SYSTEMS; TEXT PROCESSING;

RECOGNIZING TEXTUAL ENTAILMENTS; SIMILARITY MEASURE; STRING SIMILARITY; SUBTASK; SUPPORT VECTORS MACHINE; TEXTUAL ENTAILMENT;

SUPPORT VECTOR MACHINES;

EID: 84986549847     PISSN: 0736587X     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. R. Bar-Haim, I. Dagan, B. Dolan, L. Ferro, D. Giampiccolo, B. Magnini, and I. Szpektor. 2006. The 2nd PASCAL recognising textual entailment challenge. In Proceedings of the 2nd PASCAL Challenges Workshop on Recognising Textual Entailment, Venice, Italy.
2. C.-C. Chang and C.-J. Lin, 2001. LIBSVM: a library for Support Vector Machines. Software available at http://www.csie.ntu.edu.tw/∼cjlin/libsvm.
3. I. Dagan, O. Glickman, and B. Magnini. 2006. The PASCAL recognising textual entailment challenge. In Quiñonero-Candela et al., editor, MLCW 2005, LNAI, volume 3904, pages 177–190. Springer-Verlag.
4. S.M. Harabagiu, S.J. Maiorano, and M.A. Pasca. 2003. Open-domain textual question answering techniques. Natural Language Engineering, 9(3):231–267.
5. M.A. Jaro. 1995. Probabilistic linkage of large public health data file. Statistics in Medicine, 14:491–498.
6. Z. Kozareva and A. Montoyo. 2006. MLENT: The machine learning entailment system of the University of Alicante. In Proc. of 2nd PASCAL Challenges Workshop on Recognising Textual Entailment, Venice, Italy.
7. E. Newman, J. Dunnion, and J. Carthy. 2006. Constructing a decision tree classifier using lexical and syntactic features. In Proc. of 2nd PASCAL Challenges Workshop on Recognising Textual Entailment, Venice, Italy.
8. H.T. Ng, J.L.P. Kwan, and Y. Xia. 2001. Question answering using a large text database: A machine learning approach. In Proc. of Empirical Methods in Natural Language Processing, Carnegie Mellon Univ., PA.
9. D.R. Radev, J. Prager, and V. Samn. 2000. Ranking suspected answers to natural language questions using predictive annotation. In Proc. of NAACL-ANLP, pages 150–157, Seattle, WA.
10. V. Vapnik. 1998. Statistical learning theory. John Wiley.
11. W.E. Winkler. 1999. The state of record linkage and current research problems. Statistical Research Report RR99/04, US Bureau of the Census, Washington, DC.