Paper Info
Title
Normalized Semantic Web Distance.
Abstract
In this paper, we investigate the Normalized Semantic Web Distance NSWD, a semantics-aware distance measure between two concepts in a knowledge graph. Our measure advances the Normalized Web Distance, a recently established distance between two textual terms, to be more semantically aware. In addition to the theoretic fundamentals of the NSWD, we investigate its properties and qualities with respect to computation and implementation. We investigate three variants of the NSWD that make use of all semantic properties of nodes in a knowledge graph. Our performance evaluation based on the Miller-Charles benchmark shows that the NSWD is able to correlate with human similarity assessments on both Freebase and DBpedia knowledge graphs with values upï¾źto 0.69. Moreover, we verified the semantic awareness of the NSWD on a set of 20 unambiguous concept-pairs. We conclude that the NSWD is a promising measure with 1 a reusable implementation across knowledge graphs, 2 sufficient correlation with human assessments, and 3ï¾źawareness of semantic differences between ambiguous concepts.
Year
DOI
Venue
2016
10.1007/978-3-319-34129-3_5
ESWC
Field
DocType
Volume
Semantic similarity,Data mining,Kolmogorov complexity,Information retrieval,Computer science,Normalized compression distance,Semantic Web,Semantic property,Jaccard index,Social Semantic Web,Database,Computation
Conference
9678
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
11
11
Name
Order
Citations
PageRank
Tom de Nies112717.70
Christian Beecks243139.14
Fréderic Godin310210.62
Wesley De Neve452554.41
Grzegorz Stepien5111.20
dorthe arndt6124.65
Laurens De Vocht717122.13
Ruben Verborgh8630105.49
Thomas Seidl93515544.45
Erik Mannens1067199.58
Rik Van de Walle112040238.28