EntityBot: Supporting everyday digital tasks with entity recommendations

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorVuong, Tungen_US
dc.contributor.authorAndolina, Salvatoreen_US
dc.contributor.authorJacucci, Giulioen_US
dc.contributor.authorDaee, Pedramen_US
dc.contributor.authorKlouche, Khalilen_US
dc.contributor.authorSjöberg, Matsen_US
dc.contributor.authorRuotsalo, Tuukkaen_US
dc.contributor.authorKaski, Samuelen_US
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.groupauthorProfessorship Kaski Samuelen
dc.contributor.groupauthorComputer Science Professorsen
dc.contributor.groupauthorComputer Science - Artificial Intelligence and Machine Learning (AIML)en
dc.contributor.groupauthorFinnish Center for Artificial Intelligence, FCAIen
dc.contributor.groupauthorProbabilistic Machine Learningen
dc.contributor.groupauthorHelsinki Institute for Information Technology (HIIT)en
dc.contributor.organizationUniversity of Helsinkien_US
dc.contributor.organizationUniversity of Palermoen_US
dc.contributor.organizationCSC - IT Center for Science Ltd.en_US
dc.contributor.organizationUniversity of Copenhagenen_US
dc.date.accessioned2022-01-26T07:48:20Z
dc.date.available2022-01-26T07:48:20Z
dc.date.issued2021-09-13en_US
dc.description| openaire: EC/H2020/826266/EU//CO-ADAPT
dc.description.abstractEveryday digital tasks can highly benefit from systems that recommend the right information to use at the right time. However, existing solutions typically support only specific applications and tasks. In this demo, we showcase EntityBot, a system that captures context across application boundaries and recommends information entities related to the current task. The user's digital activity is continuously monitored by capturing all content on the computer screen using optical character recognition. This includes all applications and services being used and specific to individuals' computer usages such as instant messaging, emailing, web browsing, and word processing. A linear model is then applied to detect the user's task context to retrieve entities such as applications, documents, contact information, and several keywords determining the task. The system has been evaluated with real-world tasks, demonstrating that the recommendation had an impact on the tasks and led to high user satisfaction.en
dc.description.versionPeer revieweden
dc.format.extent4
dc.format.extent753-756
dc.identifier.citationVuong, T, Andolina, S, Jacucci, G, Daee, P, Klouche, K, Sjöberg, M, Ruotsalo, T & Kaski, S 2021, EntityBot : Supporting everyday digital tasks with entity recommendations . in RecSys 2021 - 15th ACM Conference on Recommender Systems . ACM, pp. 753-756, ACM International Conference on Recommender Systems, Virtual, Online, Netherlands, 27/09/2021 . https://doi.org/10.1145/3460231.3478883en
dc.identifier.doi10.1145/3460231.3478883en_US
dc.identifier.isbn9781450384582
dc.identifier.otherPURE UUID: 73f01f7c-c6fb-4fcc-a1a8-feefc4a0b55cen_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/73f01f7c-c6fb-4fcc-a1a8-feefc4a0b55cen_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85115602643&partnerID=8YFLogxKen_US
dc.identifier.otherPURE LINK: http://hdl.handle.net/10138/334390en_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/112554
dc.identifier.urnURN:NBN:fi:aalto-202201261455
dc.language.isoenen
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/826266/EU//CO-ADAPTen_US
dc.relation.ispartofACM International Conference on Recommender Systemsen
dc.relation.ispartofseriesRecSys 2021 - 15th ACM Conference on Recommender Systemsen
dc.rightsopenAccessen
dc.subject.keywordProactive information retrievalen_US
dc.subject.keywordReal-world tasksen_US
dc.subject.keywordUser intent modelingen_US
dc.titleEntityBot: Supporting everyday digital tasks with entity recommendationsen
dc.typeA4 Artikkeli konferenssijulkaisussafi

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