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  • Statistics In Transition

 

Article | 01-March-2015

SURVEY OF SEMANTIC SIMILARITY MEASURES IN PERVASIVE COMPUTING

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

Djamel Guessoum, Moeiz Miraoui, Chakib Tadj

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 1, 125–158

Article | 22-July-2019

THE EFFECT OF BINARY DATA TRANSFORMATION IN CATEGORICAL DATA CLUSTERING

This paper focuses on hierarchical clustering of categorical data and compares two approaches which can be used for this task. The first one, an extremely common approach, is to perform a binary transformation of the categorical variables into sets of dummy variables and then use the similarity measures suited for binary data. These similarity measures are well examined, and they occur in both commercial and non-commercial software. However, a binary transformation can possibly cause a loss of

Jana Cibulková, Zdenek Šulc, Sergej Sirota, Hana Rezanková

Statistics in Transition New Series, Volume 20 , ISSUE 2, 33–47

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