NDLI: "The 100 Most Influential Persons in History": A Data Mining Perspective

Content Provider	IEEE Xplore Digital Library
Author	Al-Naimi, N.M. Shaban, K.B.
Copyright Year	2011
Abstract	Data mining has been widely applied in various domains, however, there have been limited studies into discovering hidden knowledge from factual data about selected groups of people with special characteristics. It is important to mine data about such group of individuals to extract insightful knowledge that could lead to a better understanding of their personalities, in addition to further sociological conclusions. This paper presents the application and outcome of data mining techniques, namely data clustering and association rules extraction, to find common features and relations among social, environmental and socioeconomic factors from the lives of known influential individuals in history. The mining process was initiated by constructing a dataset through defining, extracting, and retrieving important known facts about these individuals from selected and reliable sources. Second, association rules discovery algorithms were applied in order to show interesting patterns and highlight relations between attributes. Finally, the data were clustered into different groups and each cluster was further analyzed to identify its most strongly defining attributes. The extracted association rules showed how some factors are related, such as the effect of environment type and order of birth in the family on the age at which the individual first engaged with their domain of influence. The clustering exercise demonstrated that influential people who grew up in families of a similar size and financial status share many similar characteristics.
Starting Page	719
Ending Page	724
File Size	266586
Page Count	6
File Format	PDF
ISBN	9781467300056
DOI	10.1109/ICDMW.2011.1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-11
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Art the 100 most influential people Clustering algorithms association rules extraction data clustering Educational institutions Feature extraction Association rules History mining of socioeconomic data
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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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