Journal of Mathematical Techniques and Computational Mathematics(JMTCM)

Department of Electrical and Computer Engineering Northwestern University, United States

Publications

• Short Communication   
  Machine Learning System Design: Multi-Model-Based Recommendation & Identification
  Author(s): Fanfei Meng*
  
  This document presents a comprehensive design framework for two machine learning systems aimed at optimizing recommendation and identification tasks in distinct domains: an Ads Ranking System and a Family-Friendly Listing Ranking System. Both systems leverage multi-modal data, advanced modeling techniques, and robust evaluation methods to achieve high performance and scalability. The Ads Ranking System prioritizes ads for user engagement and revenue optimization through short-term metrics such as Click-Through Rate (CTR), Conversion Rate (CVR), and Revenue Per Mile (RPM), alongside long-term metrics including user retention and model latency. It integrates diverse data sources, including user behavior, ad content (text, images, tabular data), and contextual information. The system employs feature engineering techniques to generate embeddings for visual, textual, and tabular .. Read More»
  

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