Challenges in user modeling and personalization

    Research output: Contribution to journalArticleAcademicpeer-review

    11 Citations (Scopus)

    Abstract

    Personalization has a long history, dating back to the 'master-apprentice' approach of individual tutoring that sought to pass on knowledge and skills from one generation to the next. Through user modeling and adaptation, we try to capture the tutor's human intelligence and turn it into artificial intelligence. Over the last decades, this research has evolved from an expert-driven approach toward a data-driven approach. This evolution comes with an interesting challenge: How can we continue to understand what an automated tutor is doing when the process of collecting and interpreting data about users is fully automated and the adaptation and recommendation decisions are 'deduced' from individual users' behavior as well as the behavior of all users combined? This article discusses the challenges of scrutability, repeatability, and meta-adaptation (aka adaptation of the adaptation), important research issues for the coming years.

    Original languageEnglish
    Article number8070896
    Pages (from-to)76-80
    Number of pages5
    JournalIEEE Intelligent Systems
    Volume32
    Issue number5
    DOIs
    Publication statusPublished - 1 Sep 2017

    Keywords

    • adaptation
    • artificial intelligence
    • intelligent systems
    • meta-adaptation
    • personalization
    • scrutability
    • user-modeling

    Fingerprint

    Dive into the research topics of 'Challenges in user modeling and personalization'. Together they form a unique fingerprint.

    Cite this