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http://dx.doi.org/10.13088/jiis.2022.28.4.287

Cryptocurrency Recommendation Model using the Similarity and Association Rule Mining  

Kim, Yechan (Business Data Analytics MBA, Dongguk University)
Kim, Jinyoung (Business Data Analytics MBA, Dongguk University)
Kim, Chaerin (Business Data Analytics MBA, Dongguk University)
Kim, Kyoung-jae (Dept. of MIS, Dongguk University Seoul)
Publication Information
Journal of Intelligence and Information Systems / v.28, no.4, 2022 , pp. 287-308 More about this Journal
Abstract
The explosive growth of cryptocurrency, led by Bitcoin has emerged as a major issue in the financial market recently. As a result, interest in cryptocurrency investment is increasing, but the market opens 24 hours and 365 days a year, price volatility, and exponentially increasing number of cryptocurrencies are provided as risks to cryptocurrency investors. For that reasons, It is raising the need for research to reduct investors' risks by dividing cryptocurrency which is not suitable for recommendation. Unlike the previous studies of maximizing returns by simply predicting the future of cryptocurrency prices or constructing cryptocurrency portfolios by focusing on returns, this paper reflects the tendencies of investors and presents an appropriate recommendation method with interpretation that can reduct investors' risks by selecting suitable Altcoins which are recommended using Apriori algorithm, one of the machine learning techniques, but based on the similarity and association rules of Bitocoin.
Keywords
Bitcoin; Cryptocurrency; Portfolio; Apriori algorithm; Similarity;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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