Title
Unilateral Jaccard similarity coefficient
Date Issued
01 January 2015
Access level
metadata only access
Resource Type
conference paper
Publisher(s)
CEUR-WS
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 Jaccard Similarity Coefficient (uJaccard), which doesn't only take into consideration the space among two points but also the semantics among them.
Start page
23
End page
27
Volume
1393
Language
English
OCDE Knowledge area
Ciencias de la información Bioinformática
Scopus EID
2-s2.0-84940108401
Source
CEUR Workshop Proceedings
Resource of which it is part
CEUR Workshop Proceedings
ISSN of the container
16130073
Conference
CEUR Workshop Proceedings
Sources of information: Directorio de Producción Científica Scopus