Evaluation System and Method for Big Data Based Commodity Investment Recommendation Algorithms Using Artificial Intelligence

摘要

The present invention relates to a system which establishes big data with regard to products of common series such as real estate, stock products, funds, bonds, lotto, sports Toto and the like and estimates a hit rate by using artificial intelligence for an algorithm which recommends a product having a high investment value among the plurality of products. The system comprises: an element evaluation unit calculating an evaluation value of element data for each product; an expected ranking calculation unit calculating a sum score by summing each of the element data after applying weight to each of the element data for each product and setting an estimated profit ranking of the product in order of the summed score; and a hit rate calculation unit calculating a hit rate of the estimated profit ranking by using an actual profit ranking and the estimated profit ranking for each product.