文章基本信息

标题：SURVEY OF SEMANTIC SIMILARITY MEASURES IN PERVASIVE COMPUTING
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作者：Djamel Guessoum ; Moeiz Miraoui ; Chakib Tadj 等
期刊名称：International Journal on Smart Sensing and Intelligent Systems
印刷版ISSN：1178-5608
出版年度：2015
卷号：8
期号：1
页码：125-158
出版社：Massey University
摘要：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.
关键词：pervasive computing; semantic similarity; context-aware; service discovery; service recommendation