{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/105821"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/105821","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Aqueduct: Task-based entry points in Android apps","abstract":"Modern smartphones offer voice assistants to ease a variety of tasks. However, the actions that can be performed by current voice assistants are limited – a predefined set of built in actions like checking the weather, and a few hooks that can be built into third-party applications. To extend assistant actions to third-party applications, the onus is on the application developers to manually add support for voice assistant integration. To improve the link between voice assistants and third-party apps, we built Aqueduct, a data driven task-based app search and task entry point discovery system for Android. We search over app UI data augmented with semantic annotations to find applications and screens within those applications that can accomplish a given task. Furthermore, Aqueduct can leverage the package name and the activity name of the discovered screen to automatically navigate users to that screen. A user study was conducted to compile a set of common smartphone tasks and evaluate the effectiveness of Aqueduct, which showed that it is effective at finding task-based entry points for a wide range of tasks. Aqueduct is also useful for augmenting search in application repositories, finding starting points for execution for task-automation systems, and even generating deep link suggestions for applications.","abstract_html":"Modern smartphones offer voice assistants to ease a variety of tasks. However, the actions that can be performed by current voice assistants are limited – a predefined set of built in actions like checking the weather, and a few hooks that can be built into third-party applications. To extend assistant actions to third-party applications, the onus is on the application developers to manually add support for voice assistant integration. To improve the link between voice assistants and third-party apps, we built Aqueduct, a data driven task-based app search and task entry point discovery system for Android. We search over app UI data augmented with semantic annotations to find applications and screens within those applications that can accomplish a given task. Furthermore, Aqueduct can leverage the package name and the activity name of the discovered screen to automatically navigate users to that screen. A user study was conducted to compile a set of common smartphone tasks and evaluate the effectiveness of Aqueduct, which showed that it is effective at finding task-based entry points for a wide range of tasks. Aqueduct is also useful for augmenting search in application repositories, finding starting points for execution for task-automation systems, and even generating deep link suggestions for applications.","abstract_has_math":false,"creators":["Sagar, Aravind"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Kumar, Ranjitha"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-11-26T20:49:30Z","date_published":"2019-11-26T20:49:30Z","updated_at":"2026-07-22T22:24:45Z","subjects":["android app entry-point","task-based app search","voice assistant actions"],"languages":["en"],"rights":["Copyright 2019 Aravind Sagar"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/105821","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kumar, Ranjitha"]},{"key":"dc:creator","label":"Author","values":["Sagar, Aravind"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-11-26T20:49:30Z","2021-11-27T10:15:27Z","2019-07-15","2019-08"]},{"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":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"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":["android app entry-point","task-based app search","voice assistant actions"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 Aravind Sagar"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/105821"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Modern smartphones offer voice assistants to ease a variety of tasks. However, the actions that can be performed by current voice assistants are limited – a predefined set of built in actions like checking the weather, and a few hooks that can be built into third-party applications. To extend assistant actions to third-party applications, the onus is on the application developers to manually add support for voice assistant integration. To improve the link between voice assistants and third-party apps, we built Aqueduct, a data driven task-based app search and task entry point discovery system for Android. We search over app UI data augmented with semantic annotations to find applications and screens within those applications that can accomplish a given task. Furthermore, Aqueduct can leverage the package name and the activity name of the discovered screen to automatically navigate users to that screen. A user study was conducted to compile a set of common smartphone tasks and evaluate the effectiveness of Aqueduct, which showed that it is effective at finding task-based entry points for a wide range of tasks. Aqueduct is also useful for augmenting search in application repositories, finding starting points for execution for task-automation systems, and even generating deep link suggestions for applications.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2021-08-01","The student, Aravind Sagar, accepted the attached license on 2019-07-15 at 12:17.","The student, Aravind Sagar, submitted this Thesis for approval on 2019-07-15 at 12:24.","This Thesis was approved for publication on 2019-07-15 at 14:11.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14321 on 2019-11-26 at 13:05:54","Made available in DSpace on 2019-11-26T20:49:30Z (GMT). No. of bitstreams: 2 SAGAR-THESIS-2019.pdf: 8647624 bytes, checksum: f94f0b48d3da9aea55f3691b1b53ec8d (MD5) LICENSE.txt: 4210 bytes, checksum: ab2ffd65bf700f93649c6a0e21d7c63a (MD5) Previous issue date: 2019-07-15","Embargo set by: Seth Robbins for item 112966 Lift date: 2021-11-26T20:49:41Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","U of I Only Restriction Lifted for Item 112966 on 2021-11-27T10:15:27Z."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Aqueduct: Task-based entry points in Android apps"]}]}],"canonical_facts":{"dc:contributor":["Kumar, Ranjitha"],"dc:creator":["Sagar, Aravind"],"dc:date":["2019-11-26T20:49:30Z","2021-11-27T10:15:27Z","2019-07-15","2019-08"],"dc:description":["Modern smartphones offer voice assistants to ease a variety of tasks. However, the actions that can be performed by current voice assistants are limited – a predefined set of built in actions like checking the weather, and a few hooks that can be built into third-party applications. To extend assistant actions to third-party applications, the onus is on the application developers to manually add support for voice assistant integration. To improve the link between voice assistants and third-party apps, we built Aqueduct, a data driven task-based app search and task entry point discovery system for Android. We search over app UI data augmented with semantic annotations to find applications and screens within those applications that can accomplish a given task. Furthermore, Aqueduct can leverage the package name and the activity name of the discovered screen to automatically navigate users to that screen. A user study was conducted to compile a set of common smartphone tasks and evaluate the effectiveness of Aqueduct, which showed that it is effective at finding task-based entry points for a wide range of tasks. Aqueduct is also useful for augmenting search in application repositories, finding starting points for execution for task-automation systems, and even generating deep link suggestions for applications.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2021-08-01","The student, Aravind Sagar, accepted the attached license on 2019-07-15 at 12:17.","The student, Aravind Sagar, submitted this Thesis for approval on 2019-07-15 at 12:24.","This Thesis was approved for publication on 2019-07-15 at 14:11.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14321 on 2019-11-26 at 13:05:54","Made available in DSpace on 2019-11-26T20:49:30Z (GMT). No. of bitstreams: 2 SAGAR-THESIS-2019.pdf: 8647624 bytes, checksum: f94f0b48d3da9aea55f3691b1b53ec8d (MD5) LICENSE.txt: 4210 bytes, checksum: ab2ffd65bf700f93649c6a0e21d7c63a (MD5) Previous issue date: 2019-07-15","Embargo set by: Seth Robbins for item 112966 Lift date: 2021-11-26T20:49:41Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","U of I Only Restriction Lifted for Item 112966 on 2021-11-27T10:15:27Z."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/105821"],"dc:language":["en"],"dc:rights":["Copyright 2019 Aravind Sagar"],"dc:subject":["android app entry-point","task-based app search","voice assistant actions"],"dc:title":["Aqueduct: Task-based entry points in Android apps"],"dc:type":["text"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:45Z"}