Multilayer Networks: For Modeling and Analysis of Big Data

Abhishek Santra, Hafsa Billah, Sharma Chakravarthy

2024

Abstract

In this position paper, we make a case for the appropriateness, utility, and effectiveness of graph models for big data analysis focusing on Multilayer Networks (or MLNs) – a specific type of graph. MLNs have been shown to be more appropriate for modeling complex data compared to their traditional counterparts. MLNs have also been shown to be useful for diverse data types, such as videos and information integration. Further, MLNs have been shown to be flexible for computing analysis objectives from diverse application domains using extant and new algorithms. There is research for automating the modeling of MLNs using widely used EER (Enhanced/Extended Entity Relationship) or Unified Modeling Language (UML) approaches. We start by discussing different graph models and their benefits and limitations. We demonstrate how MLNs can be effectively used to model applications with complex data. We also summarize the work on the use of EER models to generate MLNs in a principled manner. We elaborate on analysis alternatives provided by MLNs and their ability to match analysis needs. We show the use of MLNs for - i) traditional data analysis, ii) video content analysis, iii) complex data analysis, and iv) propose the use of MLNs for information integration or fusion. We show examples drawn from the literature of their modeling and analysis usage. We conclude that graphs, specifically MLNs provide a rich alternative to model and analyze big data. Of course, this certainly does not preclude newer data models that are likely to come along.

Paper Citation

in Harvard Style

Santra A., Billah H. and Chakravarthy S. (2024). Multilayer Networks: For Modeling and Analysis of Big Data. In Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR; ISBN 978-989-758-716-0, SciTePress, pages 383-390. DOI: 10.5220/0012997200003838

in Bibtex Style

@conference{kdir24,
author={Abhishek Santra and Hafsa Billah and Sharma Chakravarthy},
title={Multilayer Networks: For Modeling and Analysis of Big Data},
booktitle={Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR},
year={2024},
pages={383-390},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012997200003838},
isbn={978-989-758-716-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR
TI - Multilayer Networks: For Modeling and Analysis of Big Data
SN - 978-989-758-716-0
AU - Santra A.
AU - Billah H.
AU - Chakravarthy S.
PY - 2024
SP - 383
EP - 390
DO - 10.5220/0012997200003838
PB - SciTePress