Wordification: Propositionalization by unfolding relational data into bags of words
作者：
Highlights：
• We improved wordification methodology and provide a formal framework and pseudo code.
• We statistically evaluated comparable algorithms on multiple relational databases.
• Experiments show favorable results in terms of accuracy and efficiency.
• Feature simplicity is compensated by n-gram construction and by feature weighting.
• We implemented the full experimental workflow in a data mining platform ClowdFlows.
摘要
•We improved wordification methodology and provide a formal framework and pseudo code.•We statistically evaluated comparable algorithms on multiple relational databases.•Experiments show favorable results in terms of accuracy and efficiency.•Feature simplicity is compensated by n-gram construction and by feature weighting.•We implemented the full experimental workflow in a data mining platform ClowdFlows.
论文关键词：Wordification,Inductive Logic Programming,Relational Data Mining,Propositionalization,Text mining,Classification
论文评审过程：Available online 24 April 2015, Version of Record 15 May 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.04.017
