EntityBot: Supporting everyday digital tasks with entity recommendations

Tung Vuong, Salvatore Andolina, Giulio Jacucci, Pedram Daee, Khalil Klouche, Mats Sjöberg, Tuukka Ruotsalo, Samuel Kaski

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

Abstrakti

Everyday 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.

AlkuperäiskieliEnglanti
OtsikkoRecSys 2021 - 15th ACM Conference on Recommender Systems
KustantajaACM
Sivut753-756
Sivumäärä4
ISBN (elektroninen)9781450384582
DOI - pysyväislinkit
TilaJulkaistu - 13 syyskuuta 2021
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaACM International Conference on Recommender Systems - Virtual, Online, Alankomaat
Kesto: 27 syyskuuta 20211 lokakuuta 2021
Konferenssinumero: 15

Conference

ConferenceACM International Conference on Recommender Systems
LyhennettäRecSys
Maa/AlueAlankomaat
KaupunkiVirtual, Online
Ajanjakso27/09/202101/10/2021

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