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Personalized EDM Subject Generation via Co-factored User-Subject Embedding

  • Yu-Hsiu Chen,
  • Zhi Rui Tam,
  • Hong-Han Shuai

摘要

This paper introduces the Co-Factored User-Subject Embedding based Personalized EDM Subject Generation Framework (COUPES), a model for creating personalized Electronic Direct Mail (EDM) subjects. COUPES adapts to individual content and style preferences using a dual-encoder structure to process product descriptions and template features. It employs a soft template-based selective encoder and matrix co-factorization for nuanced user embeddings. Experiments show that COUPES excels in generating engaging, personalized subjects and reconstructing recommendation ratings, proving its effectiveness in personalized marketing and recommendation systems.