Exploration System and Method of Optimal Weight of Big Data-based Commodity Investment Recommendation Algorithm Using Artificial Intelligence

摘要

The present invention relates to a technology for a system of building big data with regard to commodities of a common system such as real estate, stock products, funds, bonds, lotto, sportstoto, and the like and using artificial intelligence to calculate an optimal weight set from which the best hit rate is derived so as to recommend the commodities with a high investment value among the plurality of commodities. The system comprises: an element evaluation unit calculating evaluation values of element data for each commodity; a predicted ranking calculation unit calculating a total score by applying weights to the evaluation values of each element data for each commodity and summing up the same; and a weight calculation unit calculating the hit rate of an expected profit ranking by using an actual profit ranking and the expected profit ranking for each product and deriving an optimal weight set from which the best hit rate is calculated.