Paper Info
Title
Linguistic summaries for periodicity detection based on mathematical morphology
Abstract
The paper presents a methodology to evaluate the periodicity of a temporal data series, neither relying on assumption about the series form nor requiring expert knowledge to set parameters. It exploits tools from mathematical morphology to compute a periodicity degree and a candidate period, as well as the fuzzy set theory to generate a natural language sentence, improving the result interpretability. Experiments on both artificial and real data illustrate the relevance of the proposed approach.
Year
DOI
Venue
2013
10.1109/FOCI.2013.6602462
Foundations of Computational Intelligence
Keywords
DocType
Citations 
computational linguistics,data mining,fuzzy set theory,mathematical morphology,natural language processing,candidate period computation,fuzzy set theory,linguistic summary,mathematical morphology,natural language sentence generation,periodicity degree compute,periodicity detection,temporal data series,Linguistic summaries,Mathematical morphology,Natural language generation,Periodicity computing,Temporal data mining,Temporal quantifier
Conference
11
PageRank 
References 
Authors
0.50
13
3
Name
Order
Citations
PageRank
Gilles Moyse1110.50
Marie-Jeanne Lesot2251.96
Bernadette Bouchon-Meunier3110.50