@article{Janowicz2011,
abstract = {Similarity measures have a long tradition in fields such as information retrieval, artificial intelligence, and cognitive science. Within the last years, these measures have been extended and reused to measure semantic similarity; i.e., for comparing meanings rather than syntactic differences. Various measures for spatial applications have been developed, but a solid foundation for answering what they measure; how they are best applied in information retrieval; which role contextual information plays; and how similarity values or rankings should be interpreted is still missing. It is therefore difficult to decide which measure should be used for a particular application or to compare results from different similarity theories. Based on a review of existing similarity measures, we introduce a framework to specify the semantics of similarity. We discuss similarity-based information retrieval paradigms as well as their implementation in web-based user interfaces for geographic information retrieval to demonstrate the applicability of the framework. Finally, we formulate open challenges for similarity research.},
author = {Janowicz, Krzysztof and Raubal, Martin and Kuhn, Werner},
doi = {10.5311/josis.v0i2.26},
issn = {1948-660X},
journal = {Journal of Spatial Information Science},
keywords = {SML-LIB-BIBLIO,context,description logic,geographic information retrieval,lang:ENG,ontology,relevance,semantic similarity,similarity measure,user interface},
language = {en},
mendeley-tags = {SML-LIB-BIBLIO,lang:ENG},
pages = {29--57},
title = {{The semantics of similarity in geographic information retrieval}},
url = {http://josis.net/index.php/josis/article/view/26/23},
volume = {2},
year = {2011}
}