Projekteja vuodessa
Abstrakti
Recommender systems can support everyday digital tasks by retrieving and recommending useful information contextually. This is becoming increasingly relevant in services and operating systems. Previous research often focuses on specific recommendation tasks with data captured from interactions with an individual application. The quality of recommendations is also often evaluated addressing only computational measures of accuracy, without investigating the usefulness of recommendations in realistic tasks. The aim of this work is to synthesize the research in this area through a novel approach by (1) demonstrating comprehensive digital activity monitoring, (2) introducing entity-based computing and interaction, and (3) investigating the previously overlooked usefulness of entity recommendations and their actual impact on user behavior in real tasks. The methodology exploits context from screen frames recorded every 2 seconds to recommend information entities related to the current task. We embodied this methodology in an interactive system and investigated the relevance and influence of the recommended entities in a study with participants resuming their real-world tasks after a 14-day monitoring phase. Results show that the recommendations allowed participants to find more relevant entities than in a control without the system. In addition, the recommended entities were also used in the actual tasks. In the discussion, we reflect on a research agenda for entity recommendation in context, revisiting comprehensive monitoring to include the physical world, considering entities as actionable recommendations, capturing drifting intent and routines, and considering explainability and transparency of recommendations, ethics, and ownership of data.
Alkuperäiskieli | Englanti |
---|---|
Artikkeli | 3458919 |
Sivumäärä | 41 |
Julkaisu | ACM Transactions on Computer-Human Interaction |
Vuosikerta | 28 |
Numero | 5 |
DOI - pysyväislinkit | |
Tila | Julkaistu - lokak. 2021 |
OKM-julkaisutyyppi | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä |
Sormenjälki
Sukella tutkimusaiheisiin 'Entity Recommendation for Everyday Digital Tasks'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.Projektit
- 3 Päättynyt
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Interaktiivinen koneoppiminen useista biodatalähteistä
Kaski, S. (Vastuullinen tutkija), Hämäläinen, A. (Projektin jäsen), Gadd, C. (Projektin jäsen), Hegde, P. (Projektin jäsen), Shen, Z. (Projektin jäsen), Siren, J. (Projektin jäsen), Trinh, T. (Projektin jäsen), Jain, A. (Projektin jäsen) & Jälkö, J. (Projektin jäsen)
01/01/2019 → 31/08/2021
Projekti: Academy of Finland: Other research funding
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CO-ADAPT: Adaptive Environments and Conversational Agent Based approaches for Healthy Ageing and Work Ability
Kaski, S. (Vastuullinen tutkija), Rezaei Yousefi, Z. (Projektin jäsen) & Murena, P.-A. (Projektin jäsen)
01/12/2018 → 31/05/2022
Projekti: EU: Framework programmes funding
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Interaktiivinen koneoppiminen useista biodatalähteistä
Kaski, S. (Vastuullinen tutkija) & Filstroff, L. (Projektin jäsen)
01/01/2016 → 31/08/2021
Projekti: Academy of Finland: Other research funding