Junaid Qadir

TL;DR: This paper presents a wide-ranging interdisciplinary review of literature of fields such as statistics, data mining and warehousing, machine learning, and Big Data Analytics in the context of the construction industry and discusses the future potential of such technologies across the multiple domain-specific sub-areas of theConstruction industry.

TL;DR: A contemporary survey on the methods of community detection and its applications in the various domains of real life by reviewing prevailing community detection algorithms that range from traditional algorithms to state of the art algorithms for overlapping community detection.

TL;DR: The empirical results demonstrate that the overall predictive performance of MTDF and rules-generation based on genetic algorithms performed the best as compared with the rest of the evaluated oversampling methods and rule-generation algorithms.

TL;DR: This paper attempts to systematise the various COVID-19 research activities leveraging data science, where data science is defined broadly to encompass the various methods and tools that can be used to store, process, and extract insights from data.

TL;DR: In this article, the authors provide an overview of unsupervised learning in the domain of networking, and provide a comprehensive review of the current state of the art in this area, by synthesizing insights from previous survey papers.