EVOLVING MULTI-OBJECTIVE RANKING MODELS FOR GROSS MERCHANDISE VALUE OPTIMIZATION IN E-COMMERCE

摘要

An enhanced ranking approach is used to evaluate selected metrics for various services, including search and recommendations for online marketplaces and other search engine-related applications. This includes a ranking system capable of learning neural networks which efficiently tradeoff between different business objectives. For instance, a hybridized ranking system combines the strength of relevancy focused models with the flexibility of ES via ensembling to solve multi-objective ranking problems.