Portable profiles and recommendation based media services: Will users embrace them?

Asta Bäck, Sari Vainikainen

    Research output: Contribution to journalArticleScientificpeer-review

    Abstract

    User data and user profiles are very important in current web based business models and applications. Advertising revenue is to a large extent generated based on implicit and explicit user data. We propose the use of semantic, portable and user-controllable profiles to capture and model user data that can be used for personalising media services and particularly for making recommendations.

    In this paper, we present results from four user tests where users created semantic profiles and received personalised recommendations based on these profiles. We have studied users’ expectations and requirements for profile portability as well as how users have experienced the creation of a semantic profile using different data sources. We have also studied how users experienced recommendation based media services in connection with user-controlled interest profiles. In all four test cases, users have created the profiles and received the applications using the prototypes we have developed. User feedback was gathered either through interviews or using web surveys.

    Users welcomed the idea of being able to control their profile data but they also had questions and concerns about privacy if the profile is shared between services. Users had dual concerns about the recommendations: some users were
    afraid of a too limited view if the service only relies on the user’s profile; some users were afraid of being overwhelmed by too many recommendations.
    Original languageEnglish
    Pages (from-to)157-168
    JournalJournal of Print and Media Technology Research
    Volume3
    Issue number3
    Publication statusPublished - 2013
    MoE publication typeA1 Journal article-refereed

    Keywords

    • user profiles
    • portable profiles
    • media services
    • recommendations
    • semantic web technologies
    • linked data

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