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http://dx.doi.org/10.33851/JMIS.2021.8.3.183

Implementation of Fund Recommendation System Using Machine Learning  

Park, Chae-eun (Dept. of Computer Software Engineering, Dongeui University)
Lee, Dong-seok (AI Grand ICT Research Center, Dongeui University)
Nam, Sung-hyun (Dept. of Artificial Intelligence, Dongeui University)
Kwon, Soon-kak (Dept. of Computer Software Engineering, Dongeui University)
Publication Information
Journal of Multimedia Information System / v.8, no.3, 2021 , pp. 183-190 More about this Journal
Abstract
In this paper, we implement a system for a fund recommendation based on the investment propensity and for a future fund price prediction. The investment propensity is classified by scoring user responses to series of questions. The proposed system recommends the funds with a suitable risk rating to the investment propensity of the user. The future fund prices are predicted by Prophet model which is one of the machine learning methods for time series data prediction. Prophet model predicts future fund prices by learning the parameters related to trend changes. The prediction by Prophet model is simple and fast because the temporal dependency for predicting the time-series data can be removed. We implement web pages for the fund recommendation and for the future fund price prediction.
Keywords
Fund recommend system; Machine learning; Time series data prediction;
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