Survey for Landing Generative AI in Social and E-commerce Recsys -- the Industry Perspectives

• URL: http://arxiv.org/abs/2406.06475v1
• Date: Mon, 10 Jun 2024 17:16:59 GMT
• Title: Survey for Landing Generative AI in Social and E-commerce Recsys -- the Industry Perspectives
• Authors: Da Xu, Danqing Zhang, Guangyu Yang, Bo Yang, Shuyuan Xu, Lingling Zheng, Cindy Liang,
• Abstract summary: generative AI (GAI) have presented unique opportunities for augmenting and revolutionizing industrial recommender systems (Recsys) Despite growing research efforts at the intersection of these fields, the integration of GAI into industrial Recsys remains in its infancy.
• Score: 19.754976036068907
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recently, generative AI (GAI), with their emerging capabilities, have presented unique opportunities for augmenting and revolutionizing industrial recommender systems (Recsys). Despite growing research efforts at the intersection of these fields, the integration of GAI into industrial Recsys remains in its infancy, largely due to the intricate nature of modern industrial Recsys infrastructure, operations, and product sophistication. Drawing upon our experiences in successfully integrating GAI into several major social and e-commerce platforms, this survey aims to comprehensively examine the underlying system and AI foundations, solution frameworks, connections to key research advancements, as well as summarize the practical insights and challenges encountered in the endeavor to integrate GAI into industrial Recsys. As pioneering work in this domain, we hope outline the representative developments of relevant fields, shed lights on practical GAI adoptions in the industry, and motivate future research.

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