{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/122037"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/122037","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Democratizing interaction mining","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms","abstract_has_math":false,"creators":["Arsan, Deniz"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Kumar, Ranjitha","Marinov, Darko","Jabbarvand, Reyhaneh","Nichols, Jeffrey"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-12","date_published":"2023-12","updated_at":"2026-07-22T22:25:00Z","subjects":["Interaction Mining","Mobile Apps, On-device"],"languages":["en","eng"],"rights":["Copyright 2023 Deniz Arsan"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/122037","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kumar, Ranjitha","Marinov, Darko","Jabbarvand, Reyhaneh","Nichols, Jeffrey"]},{"key":"dc:creator","label":"Author","values":["Arsan, Deniz"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-12","2023-11-30"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Interaction Mining","Mobile Apps, On-device"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Deniz Arsan"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/122037"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms","The student, Deniz Arsan, accepted the attached license on 2023-11-30 at 00:47.","The student, Deniz Arsan, submitted this Dissertation for approval on 2023-11-30 at 01:06.","This Dissertation was approved for publication on 2023-11-30 at 11:04.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20074 on 2024-03-01 at 13:15:15","In the digital landscape, defined by a multitude of mobile applications spanning various platforms, our daily lives are shaped by the quality of digital experiences. The impact of these experiences extends beyond individual satisfaction and directly influences the success of organizations, driving the need for data-driven methods to evaluate and enhance user interfaces. Traditional approaches like analytics and A/B testing, while valuable, require access to an application’s codebase, limiting their utility for external applications. In response to these limitations, interaction mining has emerged as a potent technique. Interaction mining entails the capture of design and interaction data as users engage with an application, resulting in the creation of interaction traces. However, existing interaction mining systems rely on intricate OS-level interventions to enable comprehensive data capture. This dissertation introduces On-Device Interaction Mining (ODIM), a framework that democratizes interaction mining. odim enables data capture by enabling in-the-wild interaction data collection from any Android app on personal devices, without the need for specialized hardware or modifications to the operating system. ODIM empowers researchers, designers, and industry practitioners to enhance task automation, ensure robust user privacy, and bridge the gap between analytics and UX testing. These contributions provide the tools and methodologies needed to innovate digital experiences while safeguarding user privacy. ODIM is a step towards a more accessible, principled, and privacy-conscious future for interaction mining."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Democratizing interaction mining"]}]}],"canonical_facts":{"dc:contributor":["Kumar, Ranjitha","Marinov, Darko","Jabbarvand, Reyhaneh","Nichols, Jeffrey"],"dc:creator":["Arsan, Deniz"],"dc:date":["2023-12","2023-11-30"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms","The student, Deniz Arsan, accepted the attached license on 2023-11-30 at 00:47.","The student, Deniz Arsan, submitted this Dissertation for approval on 2023-11-30 at 01:06.","This Dissertation was approved for publication on 2023-11-30 at 11:04.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20074 on 2024-03-01 at 13:15:15","In the digital landscape, defined by a multitude of mobile applications spanning various platforms, our daily lives are shaped by the quality of digital experiences. The impact of these experiences extends beyond individual satisfaction and directly influences the success of organizations, driving the need for data-driven methods to evaluate and enhance user interfaces. Traditional approaches like analytics and A/B testing, while valuable, require access to an application’s codebase, limiting their utility for external applications. In response to these limitations, interaction mining has emerged as a potent technique. Interaction mining entails the capture of design and interaction data as users engage with an application, resulting in the creation of interaction traces. However, existing interaction mining systems rely on intricate OS-level interventions to enable comprehensive data capture. This dissertation introduces On-Device Interaction Mining (ODIM), a framework that democratizes interaction mining. odim enables data capture by enabling in-the-wild interaction data collection from any Android app on personal devices, without the need for specialized hardware or modifications to the operating system. ODIM empowers researchers, designers, and industry practitioners to enhance task automation, ensure robust user privacy, and bridge the gap between analytics and UX testing. These contributions provide the tools and methodologies needed to innovate digital experiences while safeguarding user privacy. ODIM is a step towards a more accessible, principled, and privacy-conscious future for interaction mining."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/122037"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Deniz Arsan"],"dc:subject":["Interaction Mining","Mobile Apps, On-device"],"dc:title":["Democratizing interaction mining"],"dc:type":["text"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:00Z"}