Text comparison using soft cardinality

Sergio Jimenez, Fabio Gonzalez, Alexander Gelbukh

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

28 Citas (Scopus)

Resumen

The classical set theory provides a method for comparing objects using cardinality and intersection, in combination with well-known resemblance coefficients such as Dice, Jaccard, and cosine. However, set operations are intrinsically crisp: they do not take into account similarities between elements. We propose a new general-purpose method for comparison of objects using a soft cardinality function that show that the soft cardinality method is superior via an auxiliary affinity (similarity) measure. Our experiments with 12 text matching datasets suggest that the soft cardinality method is superior to known approximate string comparison methods in text comparison task.

Idioma originalInglés
Título de la publicación alojadaString Processing and Information Retrieval - 17th International Symposium, SPIRE 2010, Proceedings
Páginas297-302
Número de páginas6
DOI
EstadoPublicada - 2010
Evento17th International Symposium on String Processing and Information Retrieval, SPIRE 2010 - Los Cabos, México
Duración: 11 oct. 201013 oct. 2010

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen6393 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia17th International Symposium on String Processing and Information Retrieval, SPIRE 2010
País/TerritorioMéxico
CiudadLos Cabos
Período11/10/1013/10/10

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