Geographic-aware collaborative filtering for web service recommendation

作者：

Highlights：

• Geographical information increases the precision of mashup-API recommendations.

• Geographic locations impact the operational contexts of mashup-API invocations.

• Proximity between mashups, APIs and their neighbors influence recommendations.

• Combining geographical with functional relevance yields better performance results.

摘要

•Geographical information increases the precision of mashup-API recommendations.•Geographic locations impact the operational contexts of mashup-API invocations.•Proximity between mashups, APIs and their neighbors influence recommendations.•Combining geographical with functional relevance yields better performance results.

论文关键词：Recommendation,Location,Topic model,Implicit feedback,Matrix factorization

论文评审过程：Received 8 August 2019, Revised 18 November 2019, Accepted 27 February 2020, Available online 29 February 2020, Version of Record 9 March 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113347