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dc.contributor Gordon, V. Scott en_US
dc.contributor.advisor Baynes, Anna en_US
dc.contributor.author Vadodariya, Aaishwary Manojkumar
dc.date.accessioned 2020-03-11T15:58:22Z
dc.date.available 2020-03-11T15:58:22Z
dc.date.issued 2020-03-11
dc.date.submitted 2019-12-03
dc.identifier.uri http://hdl.handle.net/10211.3/215254
dc.description Project (M.S., Computer Science)--California State University, Sacramento, 2019. en_US
dc.description.abstract In this work, we present analytical results obtained by data mining on the START (Study of Terrorism and Response to Terrorism) dataset. The main objective is to visualize terrorism data and make it available to users in an easy to understand format. A website is designed which contains a collection of various analyses and visualizations to interpret patterns and trends in it. The website also contains a visualization tool that provides the user with dataset exploration capabilities. Lack of understanding and awareness about global terrorism leads to diverse opinions and common misconceptions among civilians. In this age of globalization, sufficient information about this topic can help strengthen our counter-terrorism strategies, improvise security concerns, regulate better economic policies and enhance the knowledge base of civilians. The primary dataset for this project is provided by START Consortium which contains data of terrorist events since 1970. Performing various data mining and data visualization techniques to interpret the nature of terrorism to better understand its trends and patterns in over 45 years of its recorded history. en_US
dc.description.sponsorship Computer Science en_US
dc.language.iso en_US en_US
dc.subject Terrorism--Prevention en_US
dc.subject Data mining en_US
dc.subject Information visualization en_US
dc.title Data mining and analysis on START dataset en_US
dc.type Project en_US


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