Stock recommendation platform based on the environment. INSIDER

Abstract

The research presented in this paper, focuses on an investment recommendation system for businesses in order to provide investment related suggestions. For this purpose, it is identified different factors that could be extracted from the internet and from the information provided by the users. Currently, the research is in its initial stage, it has been reviewed the literature on data based techniques for investment recommendations, which will provide a complete overview of the methodologies, techniques and recent developments in this field. Once the state of the art has been reviewed, the platform model developed through a virtual organization of agents, called INSIDER.