TY - GEN
T1 - Soft Cardinality + ML
T2 - 1st Joint Conference on Lexical and Computational Semantics, *SEM 2012
AU - Jimenez, Sergio
AU - Becerra, Claudia
AU - Gelbukh, Alexander
N1 - Publisher Copyright:
© 2012 Association for Computational Linguistics.
PY - 2012
Y1 - 2012
N2 - This paper presents a novel approach for building adaptive similarity functions based on cardinality using machine learning. Unlike current approaches that build feature sets using similarity scores, we have developed these feature sets with the cardinalities of the commonalities and differences between pairs of objects being compared. This approach allows the machine-learning algorithm to obtain an asymmetric similarity function suitable for directional judgments. Besides using the classic set cardinality, we used soft cardinality to allow flexibility in the comparison between words. Our approach used only the information from the surface of the text, a stop-word remover and a stemmer to address the cross-lingual textual entailment task 8 at SEMEVAL 2012. We have the third best result among the 29 systems submitted by 10 teams. Additionally, this paper presents better results compared with the best official score.
AB - This paper presents a novel approach for building adaptive similarity functions based on cardinality using machine learning. Unlike current approaches that build feature sets using similarity scores, we have developed these feature sets with the cardinalities of the commonalities and differences between pairs of objects being compared. This approach allows the machine-learning algorithm to obtain an asymmetric similarity function suitable for directional judgments. Besides using the classic set cardinality, we used soft cardinality to allow flexibility in the comparison between words. Our approach used only the information from the surface of the text, a stop-word remover and a stemmer to address the cross-lingual textual entailment task 8 at SEMEVAL 2012. We have the third best result among the 29 systems submitted by 10 teams. Additionally, this paper presents better results compared with the best official score.
UR - http://www.scopus.com/inward/record.url?scp=85041188307&partnerID=8YFLogxK
M3 - Contribución a la conferencia
AN - SCOPUS:85041188307
T3 - *SEM 2012 - 1st Joint Conference on Lexical and Computational Semantics
SP - 684
EP - 688
BT - Proceedings of the 6th International Workshop on Semantic Evaluation, SemEval 2012
PB - Association for Computational Linguistics (ACL)
Y2 - 7 June 2012 through 8 June 2012
ER -