Title: Detecting temporal changes in event sequences : An application to demographic data
Authors: Blockeel, Hendrik
Fuernkranz, Johannes
Prskawetz, Alexia
Billari, Francesco C #
Issue Date: 2001
Publisher: Springer
Host Document: Lecture notes in computer science vol:2168 pages:29-41
Conference: European Conference on Principles and Practice of Knowledge Discovery in Databases edition:5 location:Freiburg, Germany date:3-7 September 2001
Abstract: In this paper, we discuss an approach for discovering temporal changes in event sequences, and present first results from a study on demographic data. The data encode characteristic events in a person's life course, such as their birth date, the begin and end dates of their partnerships and marriages, and the birth dates of their children. The goal is to detect significant changes in the chronology of these events over people from different birth cohorts. To solve this problem, we encoded the temporal information in a first-order logic representation, and employed Warmr, an ILP system that discovers association rules in a multi-relational data set, to detect frequent patterns that show significant variance over different birth cohorts. As a case study in multi-relational association rule mining, this work illustrates the flexibility resulting from the use of first-order background knowledge, but also uncovers a number of important issues that hitherto received little attention.
ISSN: 0302-9743
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Informatics Section
# (joint) last author

Files in This Item:
File Description Status SizeFormat
35318.psarticle Published 416KbPostscriptView/Open


All items in Lirias are protected by copyright, with all rights reserved.