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Bitcoin Transaction Forecasting with Deep Network Representation Learning. (arXiv:2007.07993v2 [cs.SI] UPDATED)
cs.LG updates on arXiv.org arxiv.org
Bitcoin and its decentralized computing paradigm for digital currency trading
are one of the most disruptive technology in the 21st century. This paper
presents a novel approach to developing a Bitcoin transaction forecast model,
DLForecast, by leveraging deep neural networks for learning Bitcoin transaction
network representations. DLForecast makes three original contributions. First,
we explore three interesting properties between Bitcoin transaction accounts:
topological connectivity pattern of Bitcoin accounts, transaction amount
pattern, and transaction dynamics. Second, we construct a time-decaying
reachability graph …
arxiv bitcoin forecasting learning network representation representation learning