Related papers: A FinTech Clustering Framework: Technology, Model,…
There is a great diversity of clustering and community detection algorithms, which are key components of many data analysis and exploration systems. To the best of our knowledge, however, there does not exist yet any uniform benchmarking…
Spectral clustering has gained importance in recent years due to its ability to cluster complex data as it requires only pairwise similarity among data points with its ease of implementation. The central point in spectral clustering is the…
The explosion in the amount of data available for analysis often necessitates a transition from batch to incremental clustering methods, which process one element at a time and typically store only a small subset of the data. In this paper,…
Graph clustering is a central topic in unsupervised learning with a multitude of practical applications. In recent years, multi-view graph clustering has gained a lot of attention for its applicability to real-world instances where one has…
Text clustering serves as a fundamental technique for organizing and interpreting unstructured textual data, particularly in contexts where manual annotation is prohibitively costly. With the rapid advancement of Large Language Models…
Clustering is a fundamental data mining tool that aims to divide data into groups of similar items. Generally, intuition about clustering reflects the ideal case -- exact data sets endowed with flawless dissimilarity between individual…
The success of deep learning in recent years have led to a significant increase in interest and prevalence for its adoption to tackle financial services tasks. One particular question that often arises as a barrier to adopting deep learning…
Decentralized finance, powered by blockchain technology, is growing day by day. This field, which emerged a few years ago, today manages $70 billion in assets. In this study, the concept of decentralized finance is discussed and explained…
Container technologies have been evolving rapidly in the cloud-native era. Kubernetes, as a production-grade container orchestration platform, has been proven to be successful at managing containerized applications in on-premises…
Cloud computing has been attracting the attention of several researchers both in the academia and the industry as it provides many opportunities for organizations by offering a range of computing services. For cloud computing to become…
Cluster computing is not a new area of computing. It is, however, evident that there is a growing interest in its usage in all areas where applications have traditionally used parallel or distributed computing platforms. The growing…
This paper investigates the evolving landscape of decentralized finance (DeFi) by examining its foundational concepts, research trends, and ecosystem. A bibliometric analysis was conducted to identify thematic clusters and track the…
The economical world consists of a highly interconnected and interdependent network of firms. Here we develop temporal and structural network tools to analyze the state of the economy. Our analysis indicates that a strong clustering can be…
Intelligent information systems that contain emergent elements often encounter trust problems because results do not get sufficiently explained and the procedure itself can not be fully retraced. This is caused by a control flow depending…
Clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Clustering is the process of grouping similar…
The first generation of blockchain focused on digital currencies and secure storage, management and transfer of tokenized values. Thereafter, the focus has been shifting from currencies to a broader application space. In this paper, we…
Roughly speaking, clustering evolving networks aims at detecting structurally dense subgroups in networks that evolve over time. This implies that the subgroups we seek for also evolve, which results in many additional tasks compared to…
Smartphones have created a significant impact on the day to day activities of every individual. Now a days a wide range of Smartphone applications are available and it necessitates high computing resources in order to build these…
There are various approaches to graph learning for data clustering, incorporating different spectral and structural constraints through diverse graph structures. Some methods rely on bipartite graph models, where nodes are divided into two…
Technology has been playing a major role in our lives. One definition for technology is all the knowledge, products, processes, tools,methods and systems employed in the creation of goods or in providing services.This makes technological…