The Similarity Jury: Combining expert judgements on geographic concepts

Title: The Similarity Jury: Combining expert judgements on geographic concepts
Authors: Ballatore, Andrea
Wilson, David C.
Bertolotto, Michela
Permanent link:
Date: 15-Oct-2012
Online since: 2013-10-15T03:00:09Z
Abstract: A cognitively plausible measure of semantic similarity between geographic concepts is valuable across several areas, including geographic information retrieval, data mining, and ontology alignment. Semantic similarity measures are not intrinsically right or wrong, but obtain a certain degree of cognitive plausibility in the context of a given application. A similarity measure can therefore be seen as a domain expert summoned to judge the similarity of a pair of concepts according to her subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we first define the similarity jury as a panel of experts having to reach a decision on the semantic similarity of a set of geographic concepts. Second, we have conducted an evaluation of 8 WordNet-based semantic similarity measures on a subset of OpenStreetMap geographic concepts. This empirical evidence indicates that a jury tends to perform better than individual experts, but the best expert often outperforms the jury. In some cases, the jury obtains higher cognitive plausibility than its best expert.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: Springer
Copyright (published version): 2012 Springer
Keywords: Lexical similaritySemantic similarityGeo-semanticsExpert judgementWordNet
Subject LCSH: Semantics
Names, Geographical
DOI: 10.1007/978-3-642-33999-8_29
Language: en
Status of Item: Peer reviewed
Is part of: Castano, S. et al (eds.). Advances in Conceptual Modeling: ER 2012 Workshops CMS, ECDM-NoCoDA, MoDIC, MORE-BI, RIGiM, SeCoGIS, WISM, Florence, Italy, October 15-18, 2012. Proceedings
Conference Details: 6th International Workshop on Semantics and Conceptual Issues in Geographical Information Systems (SeCoGIS 2012) (part of ER 2012), Florence, Italy, October, 2012
ISBN: 978-3-642-33998-1
Appears in Collections:Computer Science Research Collection

Show full item record

Citations 50

Last Week
Last month
checked on Feb 12, 2019

Page view(s) 10

checked on May 25, 2018

Download(s) 20

checked on May 25, 2018

Google ScholarTM



This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.