Using consumer feedback from location-based services in PoI recommender systems for people with autism

作者：

Highlights：

• We present a model to retrieve sensory information about PoIs from consumer feedback.

• We evaluate PoI compatibility with users based on sensory aversions.

• We test compatibility-aware Recommender Systems (RS) for people with autism.

• Sensory data from consumer feedback enhances RS performance w.r.t. crowdsourced data.

• Modeling compatibility in RS enhances performance w.r.t. preferences alone.

摘要

•We present a model to retrieve sensory information about PoIs from consumer feedback.•We evaluate PoI compatibility with users based on sensory aversions.•We test compatibility-aware Recommender Systems (RS) for people with autism.•Sensory data from consumer feedback enhances RS performance w.r.t. crowdsourced data.•Modeling compatibility in RS enhances performance w.r.t. preferences alone.

论文关键词：Sensory features from reviews,Autism,Recommender systems

论文评审过程：Received 25 November 2020, Revised 11 February 2022, Accepted 22 March 2022, Available online 4 April 2022, Version of Record 11 April 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116972