Next Article in Journal
Interactive Presentation of Geo-Spatial Climate Data in Multi-Display Environments
Previous Article in Journal
Simulating Urban Growth Using a Random Forest-Cellular Automata (RF-CA) Model
Article Menu

Export Article

Open AccessArticle
ISPRS Int. J. Geo-Inf. 2015, 4(2), 471-492; doi:10.3390/ijgi4020471

A Structural-Lexical Measure of Semantic Similarity for Geo-Knowledge Graphs

1
Center for Spatial Studies, University of California, Santa Barbara, CA 93106, USA
2
School of Computer Science and Informatics, University College Dublin, Dublin 4, Ireland
3
Department of Software and Information Systems, University of North Carolina, Charlotte, NC 28223, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
Received: 24 December 2014 / Revised: 9 March 2015 / Accepted: 23 March 2015 / Published: 1 April 2015
View Full-Text   |   Download PDF [449 KB, uploaded 1 April 2015]   |  

Abstract

Graphs have become ubiquitous structures to encode geographic knowledge online. The Semantic Web’s linked open data, folksonomies, wiki websites and open gazetteers can be seen as geo-knowledge graphs, that is labeled graphs whose vertices represent geographic concepts and whose edges encode the relations between concepts. To compute the semantic similarity of concepts in such structures, this article defines the network-lexical similarity measure (NLS). This measure estimates similarity by combining two complementary sources of information: the network similarity of vertices and the semantic similarity of the lexical definitions. NLS is evaluated on the OpenStreetMap Semantic Network, a crowdsourced geo-knowledge graph that describes geographic concepts. The hybrid approach outperforms both network and lexical measures, obtaining very strong correlation with the similarity judgments of human subjects. View Full-Text
Keywords: geographic concepts; semantic similarity; geo-knowledge graphs; network-lexical similarity measure (NLS); lexical similarity; network similarity geographic concepts; semantic similarity; geo-knowledge graphs; network-lexical similarity measure (NLS); lexical similarity; network similarity
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Ballatore, A.; Bertolotto, M.; Wilson, D.C. A Structural-Lexical Measure of Semantic Similarity for Geo-Knowledge Graphs. ISPRS Int. J. Geo-Inf. 2015, 4, 471-492.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top