基于总注视时长的自动售货机智能推荐系统实验研究

Smart Recommendation System for Vending Machines Based on Total Fixation Duration

目的 如何缓解消费者面对系列文创产品的决策困难问题,辅助消费者决策并提升购物体验是无人零售领域亟待解决的问题,眼动追踪技术为无人零售的人机交互体验提供了新机遇。方法 针对文创售货机,利用眼动追踪技术提出了一种基于总注视时长的自动售货机单因素智能推荐方法,搭建了文创售货机货柜模拟场景完成实验验证。经过眼动数据分析结合主观访谈,探讨分析了该方法对消费者购买意图的预测情况,以及在不同推荐策略下的推荐效果。结果 利用此推荐方法,当推荐3个商品时,命中至少1个消费者意愿购买商品的概率为97.92%,且命中最爱商品概率为78.13%。结论 该智能推荐方法能够有效预测消费者的购买意图、缩小决策范围辅助决策,并为实现自动售货机的智能化导购提供研究基础。

How to alleviate the decision-making difficulty of consumers facing a series of cultural and creative prod-ucts and assist consumers in decision-making and improve the shopping experience is an urgent problem in the field of unmanned retail.Eye tracking technology provides new opportunities for the human-computer interaction experience of unmanned retail.A single-factor smart recommendation method for vending machines based on total fixation duration was proposed by eye tracking technology.A simulation scenario of a cultural and creative product vending machine container was constructed for experimental verification.Through eye tracking data analysis and subjective interviews,the predic-tion of purchase intention and the recommendation effectiveness under different strategies were explored and analyzed.By the recommendation method,when three products were recommended,the probability of the recommendation hitting at least one consumers'purchase intention was 97.92%,and the probability of hitting the favorite product was 78.13%.The smart recommendation method can effectively predict consumers'purchase intention,narrow the decision-making scope to assist decision-making,and provide a research foundation for achieving smart shopping guidance for vending machines.