Name
Abstract | ||
|---|---|---|
Cryptocurrencies are fungible digital assets whose market capitalization has not stopped growing since the appearance of their first use case in 2009, Bitcoin. However, one of the biggest problems facing cryptocurrencies is the enormous fluctuation of their value in the market. To help understand different patterns in cryptocurrency ecosystems, several machine learning-based solutions have been proposed in the literature. This paper aims to study in detail the solutions proposed in the literature for the detection of patterns and anomalies in cryptocurrency ecosystems. The aim is to bring together different proposals and studies to help users of this market to understand how it works. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/978-3-030-86162-9_34 | BLOCKCHAIN AND APPLICATIONS |
Keywords | DocType | Volume |
Cryptocurrencies, Price, Prediction, Survey | Conference | 320 |
ISSN | Citations | PageRank |
2367-3370 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yeray Mezquita | 1 | 0 | 0.34 |
| Ana Belén Gil González | 2 | 4 | 1.73 |
| Javier Prieto | 3 | 0 | 0.34 |
| Juan Manuel Corchado | 4 | 0 | 0.34 |