\"Crime data analysis is difficult to undertake. There are continuous efforts to analyze crime and determine ways to combat crime but that task is a complex one. Additionally, the nature of a domestic violence crime is hard to detect and even more difficult to predict. Recently police have taken steps to better classify domestic violence cases. The problem is that there is nominal research into this category of crime, possibly due to its sensitive nature or lack of data available for analysis, and therefore there is little known about these crimes and how they relate to others. The objectives of this thesis are 1) develop an indirect association rule mining algorithm from a large, publicly available data set with a focus on crimes of the domestic violence nature 2) extend the indirect association rule mining algorithm for generating indirect association rules and determine its impact\"--Leaf iv.
","abstract_html":"<p>"Crime data analysis is difficult to undertake. There are continuous efforts to analyze crime and determine ways to combat crime but that task is a complex one. Additionally, the nature of a domestic violence crime is hard to detect and even more difficult to predict. Recently police have taken steps to better classify domestic violence cases. The problem is that there is nominal research into this category of crime, possibly due to its sensitive nature or lack of data available for analysis, and therefore there is little known about these crimes and how they relate to others. The objectives of this thesis are 1) develop an indirect association rule mining algorithm from a large, publicly available data set with a focus on crimes of the domestic violence nature 2) extend the indirect association rule mining algorithm for generating indirect association rules and determine its impact"--Leaf iv.</p>","abstract_has_math":false,"creators":["Englin, Riley"],"institution":null,"degree_name":"Master of Science (MS) in Computer Science","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-01-01T08:00:00Z","date_published":"2015-01-01T08:00:00Z","updated_at":"2026-07-24T02:12:52Z","subjects":["Data mining","Association rule mining","Crime analysis","Family violence--Illinois--Chicago--Case studies","Computer Sciences"],"languages":[],"rights":["Access is available to all users"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.ewu.edu/theses/331","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Englin, Riley"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS) in Computer Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Data mining","Association rule mining","Crime analysis","Family violence--Illinois--Chicago--Case studies","Computer Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Access is available to all users"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.ewu.edu/theses/331"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["\"Crime data analysis is difficult to undertake. There are continuous efforts to analyze crime and determine ways to combat crime but that task is a complex one. Additionally, the nature of a domestic violence crime is hard to detect and even more difficult to predict. Recently police have taken steps to better classify domestic violence cases. The problem is that there is nominal research into this category of crime, possibly due to its sensitive nature or lack of data available for analysis, and therefore there is little known about these crimes and how they relate to others. The objectives of this thesis are 1) develop an indirect association rule mining algorithm from a large, publicly available data set with a focus on crimes of the domestic violence nature 2) extend the indirect association rule mining algorithm for generating indirect association rules and determine its impact\"--Leaf iv.
"]},{"key":"dc:title","label":"Title","values":["Indirect association rule mining for crime data analysis"]}]}],"canonical_facts":{"dc:creator":["Englin, Riley"],"dc:description.abstract":["\"Crime data analysis is difficult to undertake. There are continuous efforts to analyze crime and determine ways to combat crime but that task is a complex one. Additionally, the nature of a domestic violence crime is hard to detect and even more difficult to predict. Recently police have taken steps to better classify domestic violence cases. The problem is that there is nominal research into this category of crime, possibly due to its sensitive nature or lack of data available for analysis, and therefore there is little known about these crimes and how they relate to others. The objectives of this thesis are 1) develop an indirect association rule mining algorithm from a large, publicly available data set with a focus on crimes of the domestic violence nature 2) extend the indirect association rule mining algorithm for generating indirect association rules and determine its impact\"--Leaf iv.
"],"dc:identifier":["https://dc.ewu.edu/theses/331"],"dc:rights":["Access is available to all users"],"dc:subject":["Data mining","Association rule mining","Crime analysis","Family violence--Illinois--Chicago--Case studies","Computer Sciences"],"dc:title":["Indirect association rule mining for crime data analysis"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science (MS) in Computer Science"]},"updated_at":"2026-07-24T02:12:52Z"}