【Author】
Zhou, Yue; Luo, Xin; Zhou, MengChu
【Source】IEEE-CAA JOURNAL OF AUTOMATICA SINICA
【Abstract】Cryptocurrency, as a typical application scene of blockchain, has attracted broad interests from both industrial and academic communities. With its rapid development, the cryptocurrency transaction network embedding (CTNE) has become a hot topic. It embeds transaction nodes into low-dimensional feature space while effectively maintaining a network structure, thereby discovering desired patterns demonstrating involved users' normal and abnormal behaviors. Based on a wide investigation into the state-of-the-art CTNE, this survey has made the following efforts: 1) categorizing recent progress of CTNE methods, 2) summarizing the publicly available cryptocurrency transaction network datasets, 3) evaluating several widely-adopted methods to show their performance in several typical evaluation protocols, and 4) discussing the future trends of CTNE. By doing so, it strives to provide a systematic and comprehensive overview of existing CTNE methods from static to dynamic perspectives, thereby promoting further research into this emerging and important field.
【Keywords】Measurement; Systematics; Protocols; Big Data; Market research; Cryptocurrency; Blockchains; Big data analysis; cryptocurrency transaction network embedding (CTNE); dynamic network; network embedding; network representation; static network
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