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This empirical study presents the Decentralized Exchanges Comparison Service (DECS), a novel tool developed by 1inch Analytics to assess exchange efficiency in decentralized finance. The DECS utilizes swap transaction monitoring and…
Directed Acyclic Graph (DAG) is a popular approach to achieve scalability of blockchain networks. Due to its high efficiency in data communication and great scalability, DAG has been widely adopted in many applications such as Internet of…
DEX, or decentralized exchange, is a prominent class of decentralized finance (DeFi) applications on blockchains, attracting a total locked value worth tens of billions of USD today. This paper presents the first large-scale empirical study…
Enabling effective and efficient machine learning (ML) over large-scale graph data (e.g., graphs with billions of edges) can have a great impact on both industrial and scientific applications. However, existing efforts to advance…
The rise of graph analytic systems has created a need for new ways to measure and compare the capabilities of graph processing systems. The MIT/Amazon/IEEE Graph Challenge has been developed to provide a well-defined community venue for…
We curate the DeXposure dataset, the first large-scale dataset for inter-protocol credit exposure in decentralized financial networks, covering global markets of 43.7 million entries across 4.3 thousand protocols, 602 blockchains, and 24.3…
Graph data management is instrumental for several use cases such as recommendation, root cause analysis, financial fraud detection, and enterprise knowledge representation. Efficiently supporting these use cases yields a number of unique…
Temporal Graph Clustering (TGC) is a new task with little attention, focusing on node clustering in temporal graphs. Compared with existing static graph clustering, it can find the balance between time requirement and space requirement…
This paper proposes an algorithm based on a staged sliding window Transformer architecture to detect abnormal behaviors in the microstructure of the foreign exchange market, focusing on high-frequency EUR/USD trading data. The method…
Numerous studies have been conducted to investigate the properties of large-scale temporal graphs. Despite the ubiquity of these graphs in real-world scenarios, it's usually impractical for us to obtain the whole real-time graphs due to…
After the success the RecSys 2020 Challenge, we are describing a novel and bigger dataset that was released in conjunction with the ACM RecSys Challenge 2021. This year's dataset is not only bigger (~ 1B data points, a 5 fold increase), but…
Data-driven solutions for the investment industry require event-based backend systems to process high-volume financial data feeds with low latency, high throughput, and guaranteed delivery modes. At vwd we process an average of 18 billion…
NFTs (Non-Fungible Tokens) have seen significant growth since they first captured public attention in 2021. However, the NFT market is plagued by fake transactions and economic bubbles, e.g., NFT wash trading. Wash trading typically refers…
Although the automation and digitisation of anti-financial crime investigation has made significant progress in recent years, detecting insider trading remains a unique challenge, partly due to the limited availability of labelled data. To…
The Linked Data Benchmark Council's Financial Benchmark (LDBC FinBench) is a new effort that defines a graph database benchmark targeting financial scenarios such as anti-fraud and risk control. The benchmark has one workload, the…
Blockchains are significantly easing trade finance, with billions of dollars worth of assets being transacted daily. However, analyzing these networks remains challenging due to the sheer volume and complexity of the data. We introduce a…
We are living in an information era from Twitter to Fitocracy every episode of peoples life is converted to numbers. That abundance of data is also available in information technologies. From Stackoverflow to GitHub many big data sources…
In this document, we describe LDBC Graphalytics, an industrial-grade benchmark for graph analysis platforms. The main goal of Graphalytics is to enable the fair and objective comparison of graph analysis platforms. Due to the diversity of…
The rise of graph analytic systems has created a need for new ways to measure and compare the capabilities of graph processing systems. The MIT/Amazon/IEEE Graph Challenge has been developed to provide a well-defined community venue for…
Decentralized applications developed using blockchain technology provide innovative business models to serve the human race and solve existing challenges. Climate change is one of the biggest problems humanity is facing and there is a…