Paper Info
Title
The similarity jury: combining expert judgements on geographic concepts
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.
Year
DOI
Venue
2012
10.1007/978-3-642-33999-8_29
ER Workshops
Keywords
Field
DocType
geographic information retrieval,best expert,semantic similarity,expert judgement,cognitive plausibility,openstreetmap geographic concept,geographic concept,similarity jury,semantic similarity measure,similarity measure,wordnet-based semantic similarity measure,wordnet
Data mining,Lexical similarity,Similarity measure,Computer science,Subject-matter expert,Artificial intelligence,Natural language processing,Semantic similarity,Ontology alignment,Information retrieval,Similarity heuristic,Geographic information retrieval,Jury
Conference
Citations 
PageRank 
References 
5
0.40
16
Authors
3
Name
Order
Citations
PageRank
Andrea Ballatore118913.99
David C. Wilson274367.35
Michela Bertolotto386391.77