A Survey On Community Identification in Dynamic Network
- DOI
- 10.2991/978-94-6463-360-3_34How to use a DOI?
- Keywords
- Community detection; Dynamic Networks; Community Detection Algorithms
- Abstract
Identifying community in dynamic networks is a process of determining the community structure of a continuously changing network, in order to provide significant insight into its characteristics and its functionality, allowing for the exact purpose of understanding deeply the operating and crucial features of current systems and investigating their underlying processes. Static networks have been the main focus of community detection research. However, as time went on, the research drifted to more scalable networks known as dynamic networks, which is the main study in our journal, since this type of network has been in multiple crucial applications such as social media, security, and public health. Accordingly, our research will be based on recent algorithms and community detection techniques, since, as we will it proved rather be a difficult challenge, along with diving into the brains behind each algorithm, comparing the effectiveness of each process there is as of today.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Oumaima Izem AU - Youssef Zaz AU - Ali Younes AU - Nassime El Rharbi PY - 2024 DA - 2024/02/05 TI - A Survey On Community Identification in Dynamic Network BT - Proceedings of the E-Learning and Smart Engineering Systems (ELSES 2023) PB - Atlantis Press SP - 335 EP - 351 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-360-3_34 DO - 10.2991/978-94-6463-360-3_34 ID - Izem2024 ER -