Autores
Gelbukh Alexander
Título SC spectra: A linear-time soft cardinality approximation for text comparison
Tipo Congreso
Sub-tipo SCOPUS
Descripción Lecture Notes in Computer Science
Resumen Soft cardinality (SC) is a softened version of the classical cardinality of set theory. However, given its prohibitive cost of computing (exponential order), an approximation that is quadratic in the number of terms in the text has been proposed in the past. SC Spectra is a new method of approximation in linear time for text strings, which divides text strings into consecutive substrings (i.e., q-grams) of different sizes. Thus, SC in combination with resemblance coefficients allowed the construction of a family of similarity functions for text comparison. These similarity measures have been used in the past to address a problem of entity resolution (name matching) outperforming SoftTFIDF measure. SC spectra method improves the previous results using less time and obtaining better performance. This allows the new method to be used with relatively large documents such as those included in classic information retrieval collections. SC spectra method exceeded SoftTFIDF and cosine tf-idf baselines with an approach that requires no term weighing.
Observaciones 10th Mexican International Conference on Artificial Intelligence: advances in Soft Computing, MICAI 2011; Code 87491
Lugar Puebla
País Mexico
No. de páginas 213-224
Vol. / Cap. Vol. 7095, Issue 2
Inicio 2011-11-26
Fin 2011-12-04
ISBN/ISSN 978-364225329-4