Text comparison using soft cardinality

Sergio Jimenez; Fabio Gonzalez; Alexander Gelbukh

doi:10.1007/978-3-642-16321-0_31

Text comparison using soft cardinality

Sergio Jimenez, Fabio Gonzalez, Alexander Gelbukh

Centro de Investigación en Computación (CIC)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

27 Scopus citations

Abstract

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.

Original language	English
Title of host publication	String Processing and Information Retrieval - 17th International Symposium, SPIRE 2010, Proceedings
Pages	297-302
Number of pages	6
DOIs	https://doi.org/10.1007/978-3-642-16321-0_31
State	Published - 2010
Event	17th International Symposium on String Processing and Information Retrieval, SPIRE 2010 - Los Cabos, Mexico Duration: 11 Oct 2010 → 13 Oct 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6393 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th International Symposium on String Processing and Information Retrieval, SPIRE 2010
Country/Territory	Mexico
City	Los Cabos
Period	11/10/10 → 13/10/10

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10.1007/978-3-642-16321-0_31

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Jimenez, S., Gonzalez, F., & Gelbukh, A. (2010). Text comparison using soft cardinality. In String Processing and Information Retrieval - 17th International Symposium, SPIRE 2010, Proceedings (pp. 297-302). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6393 LNCS). https://doi.org/10.1007/978-3-642-16321-0_31

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abstract = "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.",

author = "Sergio Jimenez and Fabio Gonzalez and Alexander Gelbukh",

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Jimenez, S, Gonzalez, F & Gelbukh, A 2010, Text comparison using soft cardinality. in String Processing and Information Retrieval - 17th International Symposium, SPIRE 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6393 LNCS, pp. 297-302, 17th International Symposium on String Processing and Information Retrieval, SPIRE 2010, Los Cabos, Mexico, 11/10/10. https://doi.org/10.1007/978-3-642-16321-0_31

Text comparison using soft cardinality. / Jimenez, Sergio; Gonzalez, Fabio; Gelbukh, Alexander.
String Processing and Information Retrieval - 17th International Symposium, SPIRE 2010, Proceedings. 2010. p. 297-302 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6393 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Jimenez, Sergio

AU - Gonzalez, Fabio

AU - Gelbukh, Alexander

PY - 2010

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N2 - 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.

AB - 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.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - String Processing and Information Retrieval - 17th International Symposium, SPIRE 2010, Proceedings

T2 - 17th International Symposium on String Processing and Information Retrieval, SPIRE 2010

Y2 - 11 October 2010 through 13 October 2010

ER -

Text comparison using soft cardinality

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