大数据驱动的企业与用户互动创新推荐系统及应用

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Abstract Big data driven enterprise-user interaction innovation is a basic form of digitized enterprise-user interaction innovation， and digitized enterprise-user interaction innovation is an innovation mode of digital economy. The innovation-oriented recommender system is a tool for digitized enterprise-user interaction innovation. Different from user-centric recommendation systems， this article focuses on recommender systems for enterprise-user interaction innovation， and analyzes the requirements of enterprise-user interactive innovation recommender system from three aspects of data， system characteristics and application evaluation. It proposes a recommender system design framework consisting of four parts： application scenarios， data basis， recommendation system characteristics and system evaluation. This framework analyzes the influence of product innovation tasks on the innovation scenarios， and the influence of product attributes and application modules on the design of recommendation systems in marketing scenarios， so as to offer guidance to the design of Big Data Driven Recommender System for Enterprise-User Interaction Innovation.

Key words： big data recommender system enterprise-user interaction innovation system design

Received: 27 November 2022

PACS:

F424.3

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	Articles by authors
	LUO Ting-yu
	XIE Kang
	LIU Yi

Cite this article:

LUO Ting-yu,XIE Kang,LIU Yi. Big Data Driven Recommender System for Enterprise-User Interaction Innovation[J]. journal6, 2023, 22(1): 33-45.

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http://xbsk.bjtu.edu.cn/EN/ OR http://xbsk.bjtu.edu.cn/EN/Y2023/V22/I1/33

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