Now showing 1 - 2 of 2
  • Publication
    Towards Activity Recommendation from Lifelogs
    With the increasing availability of passive, wearable sensor devices, digital lifelogs can now be captured for individuals. Lifelogs contain a digital trace of a person’s life, and are characterised by large quantities of rich contextual data. In this paper, we propose a content based recommender system to leverage such lifelogs to suggest activities to users. We model lifelogs as timelines of chronological sequences of activity objects, and describe a recommendation framework in which a two-level distance metric is proposed to measure the similarity between current and past timelines. An initial evaluation of our activity recommender performed using a real-world lifelog dataset demonstrates the utility of our approach.
    Scopus© Citations 9  332
  • Publication
    Towards the Recommendation of Personalised Activity Sequences in the Tourism Domain
    In this paper we consider the problem of recommending sequencesof activities to a user. The proposed approach leverages the order aswell as the context associated with the users past activity patternsto make recommendations. This work extends the general activityrecommendation framework proposed in [16] to iteratively recommendthe next sequence of activities to perform. We demonstratethe efficacy of our recommendation framework by applying it to thetourism domain and evaluations are performed using a real-world(checkin) dataset
      264