Exploiting User Movements to Derive Recommendations in Large Facilities.
DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE(2019)
摘要
This paper provides an innovative approach for taking advantage of user's movement data as implicit user feedback for deriving recommendations in large facilities. By means of a real-world museum scenario a beacon infrastructure for tracking sojourn times is presented. Then we show how sojourn times can be integrated in a collaborative filtering algorithm approach in order to outcome accurate recommendations.
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关键词
Context-aware recommender systems,Collaborative filtering,Beacon technology
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