A comprehensive study on the effects of using data mining techniques to predict tie strength
作者：
Highlights：
• The problem of tie strength is modeled as a data mining problem.
• Different supervised and unsupervised mining methods are used.
• We propose a comprehensive study on the effects of using different classification techniques.
• Several models are created and their efficiencies are compared based on F-Measure and executing time.
• Profile-behavioral based model has better accuracy than profile-data based models techniques.
摘要
•The problem of tie strength is modeled as a data mining problem.•Different supervised and unsupervised mining methods are used.•We propose a comprehensive study on the effects of using different classification techniques.•Several models are created and their efficiencies are compared based on F-Measure and executing time.•Profile-behavioral based model has better accuracy than profile-data based models techniques.
论文关键词：Data mining,Tie strength,Profile-behavioral based model,Classification techniques
论文评审过程：Received 16 October 2015, Revised 23 February 2016, Accepted 24 February 2016, Available online 4 March 2016, Version of Record 4 March 2016.
论文官网地址：https://doi.org/10.1016/j.chb.2016.02.092
