Publikationer från Malmö universitet
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The UX of Interactive Machine Learning
Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3).ORCID-id: 0000-0003-1852-3937
Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).ORCID-id: 0000-0002-9471-8405
Pennsylvania State University.
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).ORCID-id: 0000-0001-5676-1931
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2020 (engelsk)Inngår i: NordiCHI 2020, 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society, New York, USA: Association for Computing Machinery (ACM), 2020, artikkel-id Article No.: 138Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Machine Learning (ML) has been a prominent area of research within Artificial Intelligence (AI). ML uses mathematical models to recognize patterns in large and complex data sets to aid decision making in different application areas, such as image and speech recognition, consumer recommendations, fraud detection and more. ML systems typically go through a training period in which the system encounters and learns about the data; further, this training often requires some degree of human intervention. Interactive machine learning (IML) refers to ML applications that depend on continuous user interaction. From an HCI perspective, how humans interact with and experience ML models in training is the main focus of this workshop proposal. In this workshop we focus on the user experience (UX) of Interactive Machine Learning, a topic with implications not only for usability but also for the long-term success of the IML systems themselves.

sted, utgiver, år, opplag, sider
New York, USA: Association for Computing Machinery (ACM), 2020. artikkel-id Article No.: 138
Emneord [en]
UX, User Experience, Machine Learning, Artificial Intelligence, Interaction Design
HSV kategori
Forskningsprogram
Interaktionsdesign
Identifikatorer
URN: urn:nbn:se:mau:diva-24079DOI: 10.1145/3419249.3421236Scopus ID: 2-s2.0-85123040796OAI: oai:DiVA.org:mau-24079DiVA, id: diva2:1485021
Konferanse
NordiCHI 2020, 11th Nordic Conference on Human-Computer Interaction
Forskningsfinansiär
Knowledge FoundationTilgjengelig fra: 2020-10-31 Laget: 2020-10-31 Sist oppdatert: 2024-02-05bibliografisk kontrollert

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Forlagets fulltekstScopushttps://dl.acm.org/doi/abs/10.1145/3419249.3421236

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Ghajargar, MalihehPersson, Jan A.Holmberg, LarsTegen, Agnes

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Ghajargar, MalihehPersson, Jan A.Holmberg, LarsTegen, Agnes
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Totalt: 283 treff
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