Evidential estimation of event locations in microblogs using the Dempster–Shafer theory
作者：
Highlights：
• We estimate locations of events detected in Twitter using Dempster-Shafer theory.
• Our method combines evidence from multiple tweet features using combination rules.
• Our method is applicable to any event type and does not require training.
• Comparisons were made with the Bayesian methods under different settings.
• Estimations are made for two levels of location granularity with enhanced accuracy.
摘要
•We estimate locations of events detected in Twitter using Dempster-Shafer theory.•Our method combines evidence from multiple tweet features using combination rules.•Our method is applicable to any event type and does not require training.•Comparisons were made with the Bayesian methods under different settings.•Estimations are made for two levels of location granularity with enhanced accuracy.
论文关键词：location estimation,Microblogs,Event location,Dempster–Shafer theory,Evidential reasoning
论文评审过程：Received 24 July 2015, Revised 23 April 2016, Accepted 10 June 2016, Available online 4 July 2016, Version of Record 28 September 2016.
论文官网地址：https://doi.org/10.1016/j.ipm.2016.06.001
