Browsing by Author "Barraza-Urbina, Andrea"

Now showing items 1-6 of 6

    • BEARS: Towards an evaluation framework for bandit-based interactive recommender systems 

      Barraza-Urbina, Andrea; Koutrika, Georgia; d'Aquin, Mathieu,; Hayes, Conor (NUI Galway, 2018-10-06)
      Recommender Systems (RS) deployed in fast-paced dynamic scenarios must quickly learn to adapt in response to user evaluative feedback. In these settings, the RS faces an online learning problem where each decision should ...

    • Towards sharing task environments to support reproducible evaluations of interactive recommender systems 

      Barraza-Urbina, Andrea; d'Aquin, Mathieu (NUI Galway, 2019-09-20)
      Beyond sharing datasets or simulations, we believe the Recommender Systems (RS) community should share Task Environments. In this work, we propose a high-level logical architecture that will help to reason about the core ...

    • Using social media data for online television recommendation services at RTÉ Ireland 

      Barraza-Urbina, Andrea; Hromic, Hugo; Heitmann, Benjamin; Hayes, Conor; Hulpus, Ioana (2015-09)
      Raidió Teilifís Éireann (RTÉ) is the public service television and radio broadcaster in Ireland. Through on demand video services, RTÉ allows their users to catch up on television broadcasts via the RTÉ Player. The company ...

    • Using social media for online television adaptation services at RTÉ Ireland 

      Barraza-Urbina, Andrea; Hromic, Hugo; Heitmann, Benjamin; Tamatam, Himasagar; Yañez, Andrea; Hayes, Conor (Insight Centre for Data Analytics, National University of Ireland, Galway, 2016)
      RTÉ (Raidió Teilifís Éireann) is the national provider of Television (TV) and radio in Ireland. RTÉ broadcasts its content online through the RTÉ Player and provides services to interact with its users using social media, ...

    • XPLODIV: An exploitation-exploration aware diversification approach for Recommender Systems 

      Barraza-Urbina, Andrea; Heitmann, Benjamin; Hayes, Conor; Carrillo-Ramos, Angela (AAAI Press, 2015-07)
      Recommender Systems (RS) have emerged to guide users in the task of efficiently browsing/exploring a large product space, helping users to quickly identify interesting products. However, suggestions generated with traditional ...

    • XploDiv: Diversification Approach for Recommender Systems 

      Barraza-Urbina, Andrea; Heitmann, Benjamin; Hayes, Conor; Ramos, Angela Carrillo (INSIGHT Centre for Data Analytics, National University of Ireland, Galway, 2015)
      Recommender Systems have emerged to guide users in the task of efficiently browsing/exploring a large product space, helping users to quickly identify interesting products. However, suggestions generated with traditional ...