SURVEY OF SEMANTIC SIMILARITY MEASURES IN PERVASIVE COMPUTING

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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

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VOLUME 8 , ISSUE 1 (March 2015) > List of articles

SURVEY OF SEMANTIC SIMILARITY MEASURES IN PERVASIVE COMPUTING

Djamel Guessoum * / Moeiz Miraoui * / Chakib Tadj

Keywords : pervasive computing, semantic similarity, context-aware, service discovery, service recommendation

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 8, Issue 1, Pages 125-158, DOI: https://doi.org/10.21307/ijssis-2017-752

License : (CC BY-NC-ND 4.0)

Received Date : 06-October-2014 / Accepted: 08-January-2015 / Published Online: 01-March-2015

ARTICLE

ABSTRACT

Semantic similarity measures usage is prevalent in pervasive computing with the following aims: 1) to compare the components of an application; 2) to recommend and rank services by degree of relevance; 3) to identify services by matching the description of a query with the available services; 5) to compare the current context with already known contexts. The existing works that apply semantic similarity measures to pervasive computing focus on one particular issue. Furthermore, surveys in this domain are limited to the recommendation or discovery of context-aware services. In this article, we therefore present a survey of context-aware semantic similarity measures used in various areas of pervasive computing.

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