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OLAP operators for social network analysis

Ben Kraiem, Maha and Alqarni, Mohamed and Feki, Jamel and Ravat, Franck OLAP operators for social network analysis. (2019) Cluster Computing, 23. 2347-2374. ISSN 1386-7857

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Official URL: https://doi.org/10.1007/s10586-019-03006-z


The multidimensional data model and implementations of social networks come with a set of specific constraints, such as missing data, reflexive relationship on fact instance. However, the conventional OLAP operators and existing models do not provide solutions for handling those specificities. Therefore, we should invest further efforts to extend these operators to take into consideration the specificities of multidimensional modeling of tweets as well as their manipulation. Face to this issue, we propose, in this paper, new OLAP operators that enhance existing solutions for OLAP analyses involving a reflexive relationship on the fact instances and dealing with missing values on dimension members. For each OLAP operator, we suggest a user-oriented definition as an algebraic formalization, along with an implementation algorithmic.

Item Type:Article
HAL Id:hal-02923943
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > University of Jeddah (SAUDI ARABIA)
Other partners > Université de Sfax (TUNISIA)
Laboratory name:
Deposited On:27 Aug 2020 13:41

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