@inproceedings{819ed4bc1b2748faaa3bc4b3f3201047,
title = "Finding novel event relationships in temporal data",
abstract = "A path formula of the form 'A is followed by B in t time units'-where A and B can themselves be path formulas-is a common syntactical construct in a variety of temporal logic paradigms. We study the problem of mining for such formulas that frequently occur in time-series data in a manner that enables the discovery of complex relationships. This paper introduces a semantics that resembles categorical time series data, a syntax for such formulas that are annotated by the support for which such relationships occur in a time series, and provide algorithms that are capable of mining these relationships. We present several properties of this framework-both exploring worst case scenarios and presenting correct pruning techniques for our mining algorithms. The approach is then demonstrated with an implementation where we mine such relationships from two real-world datasets.",
keywords = "Frequent pattern mining, Inductive logic, Modal logic, Temporal data",
author = "Ashkan Aleali and Mahila Dadfarnia and Paulo Shakarian",
note = "Funding Information: Some of the authors are supported through the ARO grant W911NF-15-1-0282 and the DoD Minerva program. Publisher Copyright: {\textcopyright} 2018 IEEE.; 1st International Conference on Data Intelligence and Security, ICDIS 2018 ; Conference date: 08-04-2018 Through 10-04-2018",
year = "2018",
month = may,
day = "25",
doi = "10.1109/ICDIS.2018.00009",
language = "English (US)",
series = "Proceedings - 2018 1st International Conference on Data Intelligence and Security, ICDIS 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "9--16",
booktitle = "Proceedings - 2018 1st International Conference on Data Intelligence and Security, ICDIS 2018",
}