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An Evaluation of Bitcoin Address Classification based on Transaction History Summarization

https://doi.org/10.1109/bloc.2019.8751410

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting

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Exchange Pattern Mining in the Bitcoin Transaction Directed Hypergraph

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Quantitative Analysis of the Full Bitcoin Transaction Graph

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Evaluating User Privacy in Bitcoin

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Random Forests

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The perceptron: A probabilistic model for information storage and organization in the brain.

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Support vector machines

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A first estimation of the proportion of cybercriminal entities in the bitcoin ecosystem using supervised machine learning

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A Survey on Security and Privacy Issues of Bitcoin

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Data Mining for Detecting Bitcoin Ponzi Schemes

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Multi-Class Bitcoin-Enabled Service Identification Based on Transaction History Summarization

inferredcites →https://doi.org/10.1109/glocom.2017.8254420openalex-snapshot

Identification of High Yielding Investment Programs in Bitcoin via Transactions Pattern Analysis

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Characterizing Entities in the Bitcoin Blockchain

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Unsupervised learning for robust Bitcoin fraud detection

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A fistful of bitcoins

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XGBoost

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SMOTE: Synthetic Minority Over-sampling Technique

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Bitcoin: A Peer-to-Peer Electronic Cash System

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Breaking Bad: De-Anonymising Entity Types on the Bitcoin Blockchain Using Supervised Machine Learning

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Multi-class AdaBoost

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Scikit-learn: Machine Learning in Python

What points at this work

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Cryptocurrencies as a subject of financial fraud

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