Supporting scientific knowledge discovery with extended, generalized Formal Concept Analysis
作者：
Highlights：
• We present a methodology for scientific enquiry based in Formal Concept Analysis.
• We adopt the “Landscapes of Knowledge” metaphor for Exploratory Data Analysis.
• We provide use cases to demonstrate the affordances of the methodology.
• The use cases encompass gene expression data and classifier assessment.
• The use cases also include abstract algebra and information extraction and indexing.
摘要
•We present a methodology for scientific enquiry based in Formal Concept Analysis.•We adopt the “Landscapes of Knowledge” metaphor for Exploratory Data Analysis.•We provide use cases to demonstrate the affordances of the methodology.•The use cases encompass gene expression data and classifier assessment.•The use cases also include abstract algebra and information extraction and indexing.
论文关键词：Scientific knowledge discovery,Exploratory Data Analysis,Landscapes of Knowledge,Metaphor theory,Formal Concept Analysis,K-Formal Concept Analysis,Extended Formal Concept Analysis,Semiring theory,Confusion matrix,Relation extraction,Gene expression data
论文评审过程：Received 22 March 2015, Revised 15 September 2015, Accepted 17 September 2015, Available online 28 September 2015, Version of Record 10 November 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.09.022
