POSTER| Address2vec: Generating Vector Embeddings for Blockchain Analytics

dc.contributor.authorHussein, Ali
dc.contributor.authorNalwooga, Samiiha
dc.date.accessioned2024-03-21T07:56:33Z
dc.date.available2024-03-21T07:56:33Z
dc.date.issued2019-05-17
dc.description.abstractBitcoin Blockchain is a completely public open currency transaction ledger, recent growth in the crypto-currency market has driven many lawful and blackmarket actors using Bitcoin as the main method of payment. I propose address2vec an algorithm to generate vector representations of addresses on the Bitcoin Blockchain. I am able to present better results than a baseline random approach in predicting hoarding vs spending behaviour. The current work allows for utilization of common machine learning algorithms on bitcoin transaction addresses.
dc.description.provenanceSubmitted by Grace Kambwiri (gracekambwiri@gmail.com) on 2024-03-21T07:56:33Z No. of bitstreams: 1 conference_poster_2_final.pdf: 1960518 bytes, checksum: cb360b67987da15509c90f0f18169b1c (MD5)en
dc.description.provenanceMade available in DSpace on 2024-03-21T07:56:33Z (GMT). No. of bitstreams: 1 conference_poster_2_final.pdf: 1960518 bytes, checksum: cb360b67987da15509c90f0f18169b1c (MD5) Previous issue date: 2019-05-17en
dc.identifier.doihttps://doi.org/10.31730/osf.io/9pcmn
dc.identifier.doihttps://doi.org/10.60763/africarxiv/1124
dc.identifier.urihttps://africarxiv.ubuntunet.net/handle/1/1171
dc.subjectgraph embeddings
dc.subjectnode2vec
dc.subjectrepresentation learning
dc.subjectword2vec
dc.titlePOSTER| Address2vec: Generating Vector Embeddings for Blockchain Analytics

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