Title
Unilateral weighted Jaccard coefficient for NLP
Date Issued
08 March 2016
Access level
metadata only access
Resource Type
conference paper
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
Similarity measures are essential to solve many pattern recognition problems such as classification, clustering, and retrieval problems. Various similarity measures are categorized in both syntactic and semantic relationships. In this paper we present a novel similarity, Unilateral Weighted Jaccard Coefficient (uwJaccard), which takes into consideration not only the space among two points but also the semantics among them in a distributional semantic model, the Unilateral Weighted Jaccard Coefficient provides a measure of uncertainty which will be able to measure the uncertainty among sentences such as "man bites dog" and "dog bites man".
Start page
14
End page
20
Language
English
OCDE Knowledge area
Ciencias de la información Ciencias de la computación
Scopus EID
2-s2.0-84987810721
Resource of which it is part
Proceedings - 14th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence, MICAI 2015
ISBN of the container
9781509003235
Conference
Proceedings - 14th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence, MICAI 2015
Sources of information: Directorio de Producción Científica Scopus