Information recommendation system and method

Abstract

The invention provides an information recommendation system and method. The system comprises a basic data collection device, a data warehouse processing device, a basic recommendation engine device and a recommendation engine optimization device, wherein the basic data collection device is used for collecting the historical data of client browsing information and purchasing information from a financial enterprise system, wherein the historical data comprises structured data and unstructured data; the data warehouse processing device is used for receiving the historical data, converting the unstructured data into the structured data and carrying out data cleaning processing on the converted structured data and unstructured data; the basic recommendation engine device is used for calculatinga relationship between a client and a preference commodity according to the client browsing information and purchasing information in the historical data subjected to the data cleaning processing inpreset time, and obtaining a preliminary recommendation result according to the relationship between the client and the preference commodity; the recommendation engine optimization device is used forregulating the preliminary recommendation result according to a recommendation accuracy optimization regulation factor to obtain a final recommendation result, and providing the final recommendation result for a client side server. By use of the above technical scheme, information recommendation accuracy is improved.

Description

technical field [0001] The present invention relates to the technical field of information recommendation, in particular to an information recommendation system and method. Background technique [0002] E-commerce platforms have become mainstream media due to their advantages of intelligence and convenience, and have a large number of customer resources and information. Recently, more and more e-commerce platforms have connected customer information and fund receipts and payments, realizing the integration of sales, promotion, and payment, and to some extent replaced the traditional financial industry. Under the impact of such e-commerce financialization, the financial industry has also begun to set foot in the e-commerce field. How to use its rich customer data resources, discover potential purchasing power of customers, tap potential customers, and guide customers to intelligent consumption has become a new challenge. At present, the financial e-commerce platform realize...

AI Technical Summary

Problems solved by technology

[0003] Massive basic data and recommendation output results are not equal: customer basic data in the financial industry has natural advantages, including customer credit, customer assets and liabilities and other information, but the current recommendation system fails to use this part of data to construct targeted recommendations engine, failed to realize personalized recommendation, resulting in the recommendation results not matching the actual needs of customers, and the recommendation accuracy is not enough

[0004] Therefore, the recommendation accuracy of the existing information recommendation system is low

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