NDLI: Comparative Study of Association Rule Mining and MiSTIC in Extracting Spatio-temporal Disease Occurrences Patterns

Content Provider	IEEE Xplore Digital Library
Author	Raheja, V. Rajan, K.S.
Copyright Year	2012
Abstract	Extracting interesting and useful patterns from spatio-temporal datasets is more difficult than extracting the corresponding patterns from traditional numeric and categorical data due to the complexity of spatial data types and the embedded topologies, spatial and temporal relationships, and spatial autocorrelation. The objective of epidemiology is to identify disease causes and correlating them to spatially explicit disease patterns and variations in health risks. The main issue in traditional mining of association rules in disease surveillance data is that a large number of rules are discovered, but most of them are of limited use in addressing the stated objectives or original questions asked. Moreover, not all of the generated rules are interesting (due to their inability to conclusively mine spatio-temporal prevalence and causative factors of diseases), and some rules may be ignored. These drawbacks result as these methods ignore the inherent spatio-temporal dependency in such data. This paper makes a case for the use of MiSTIC algorithm to address these issues, compare the use of traditional association rule mining in context of Salmonellosis disease management, and share new insights. An illustrative case study presented here suggests that in comparison to traditional association rule mining, even simple spatio-temporal data mining approaches taking into consideration the spatio-temporal interdependencies in disease data, can provide new and valuable scientific insights towards efficient disease surveillance and management.
Starting Page	813
Ending Page	820
File Size	741404
Page Count	8
File Format	PDF
ISBN	9781467351645
e-ISBN	9781467351645
DOI	10.1109/ICDMW.2012.131
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-10
Publisher Place	Belgium
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Association Rule Mining Correlation Surveillance MiSTIC Sociology Spatio-temporal Mining Spatial databases Association rules Epidemiology Pattern extraction Diseases
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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