Towards a granular computing approach based on Formal Concept Analysis for discovering periodicities in data

作者：

Highlights：

• The adoption of Granular Computing paradigm for discovering event periodicities in temporal data.

• The adoption of Formal Concept Analysis with time-related attributes to realize granulations of data with respect to periodic time slots.

• The adoption of a set of measures to assess granulations and resulting granules according to their capability to elicit useful knowledge.

• The definition of a case study realized by using a dataset related to forest fires occurred in the natural park of Montesinho.

摘要

•The adoption of Granular Computing paradigm for discovering event periodicities in temporal data.•The adoption of Formal Concept Analysis with time-related attributes to realize granulations of data with respect to periodic time slots.•The adoption of a set of measures to assess granulations and resulting granules according to their capability to elicit useful knowledge.•The definition of a case study realized by using a dataset related to forest fires occurred in the natural park of Montesinho.

论文关键词：Formal concept analysis,Temporal data,Periodicity,Knowledge discovery,Granular computing

论文评审过程：Received 11 September 2017, Revised 24 January 2018, Accepted 29 January 2018, Available online 8 February 2018, Version of Record 28 February 2018.

论文官网地址：https://doi.org/10.1016/j.knosys.2018.01.032