EntityBot: Supporting everyday digital tasks with entity recommendations
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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.
Originalsprog | Engelsk |
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Titel | RecSys 2021 - 15th ACM Conference on Recommender Systems |
Antal sider | 4 |
Forlag | Association for Computing Machinery, Inc. |
Publikationsdato | 13 sep. 2021 |
Sider | 753-756 |
ISBN (Elektronisk) | 9781450384582 |
DOI | |
Status | Udgivet - 13 sep. 2021 |
Begivenhed | 15th ACM Conference on Recommender Systems, RecSys 2021 - Virtual, Online, Holland Varighed: 27 sep. 2021 → 1 okt. 2021 |
Konference
Konference | 15th ACM Conference on Recommender Systems, RecSys 2021 |
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Land | Holland |
By | Virtual, Online |
Periode | 27/09/2021 → 01/10/2021 |
Sponsor | ACM Special Interest Group on Artificial Intelligence (SIGAI), ACM Special Interest Group on Computer-Human Interaction (SIGCHI), ACM Special Interest Group on Hypertext, Hypermedia, and Web (ACM Special Interest Group on Hypertext, Hypermedia, and Web), ACM Special Interest Group on Information Retrieval (SIGIR), ACM Special Interest Group on Knowledge Discovery in Data (SIGKDD), Special Interest Group on Economics and Computation (SIGecom) |
Navn | RecSys 2021 - 15th ACM Conference on Recommender Systems |
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Bibliografisk note
Publisher Copyright:
© 2021 Owner/Author.
ID: 306689214