2021/02/27 by B. D. M. De Zoysa, De Zoysa, B. D. M., Yeakob Ali +9
Computer Science · #Algorithms and Data Compression #Data Mining Algorithms and Applications #Distributed #FOS: Computer and information sciences #Graph Theory and Algorithms #Information Retrieval (cs.IR) #Parallel #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.2103.00154
openalex publication_date 2021/02/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The problem of finding dense components of a graph is a widely explored area in data analysis, with diverse applications in fields and branches of study including community mining, spam detection, computer security and bioinformatics. This research project explores previously available algorithms in order to study them and identify potential modifications that could result in an improved version with considerable performance and efficiency leap. Furthermore, efforts were also steered towards devising a novel algorithm for the problem of densest subgraph discovery. This paper presents an improved implementation of a widely used densest subgraph discovery algorithm and a novel parallel algorithm which produces better results than a 2-approximation.