OLAP operators for social network analysis

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. There...

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Bibliographic Details
Published in:Cluster computing 2020-09, Vol.23 (3), p.2347-2374
Main Authors: Ben Kraiem, Maha, Alqarni, Mohamed, Feki, Jamel, Ravat, Franck
Format: Article
Language:English
Subjects:
Algorithms
Computer Communication Networks
Computer Science
Data models
Data Structures and Algorithms
Data warehouses
Efficiency
Missing data
Multidimensional data
Network analysis
Numerical Analysis
Online analytical processing
Operating Systems
Operators
Optimization
Processor Architectures
Social and Information Networks
Social network analysis
Social networks
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Summary: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.
ISSN:1386-7857
1573-7543
DOI:10.1007/s10586-019-03006-z