大数据驱动的企业与用户互动创新推荐系统及应用

Big Data Driven Recommender System for Enterprise-User Interaction Innovation

大数据驱动的企业与用户互动创新构成企业与用户数据化互动创新的基本形式,企业与用户数据化互动创新构成数字经济创新模式之一。面向创新的推荐系统是企业与用户数据化互动创新的工具,区别于以用户为中心的推荐系统,本文聚焦探讨面向企业-用户互动创新的推荐系统,从数据、系统特征和应用评估三方面分析面向企业-用户互动创新推荐系统的需求,提出由应用场景、数据基础、推荐系统特征及系统评估四部分组成的推荐系统设计框架。该框架分析了产品创新任务对于创新场景、产品属性和应用模块对于营销场景下推荐系统设计的影响,为大数据驱动的企业与用户互动创新推荐系统设计提供指导。

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.