CLEF NewsREEL 2016: Image-based Recommendation

Francesco Corsini, Martha Larson

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review


Our approach to the CLEF NewsREEL 2016 News RecommendationEvaluation Lab investigates the connection between imagesand users clicking behavior. Our goal is to gain a better understanding ofthe contribution of visual representations accompanying images (thumbnails)to the success of news recommendation algorithms as measured bystandard metrics. We experiment with visual information, namely FaceDetection and Saliency Map, extracted from the images that accompanynews items to see if they can be used to chose news items that have ahigher chance of being clicked by users. Initial results seems to suggestgreat CTR improvement in the Simulated Environment task, while somedecrease in performance has been found in the Living Lab task. Thelatter result must be further validated in the future.
Original languageEnglish
Title of host publicationCLEF 2016 Working Notes
Subtitle of host publicationConference and Labs of the Evaluation Forum
EditorsKrisztian Balog, Linda Cappellato, Nicola Ferro, Craig Macdonald
Number of pages10
Publication statusPublished - 2016
EventCLEF 2016 - Conference and Labs of the Evaluation Forum: Information Access Evaluation meets Multilinguality, and Interaction - University of Évora, Évora, Portugal
Duration: 5 Sep 20168 Sep 2016
Conference number: 7th

Publication series

NameCEUR Workshop Proceedings
ISSN (Electronic)1613-0073


ConferenceCLEF 2016 - Conference and Labs of the Evaluation Forum
Internet address


  • Recommender System
  • News
  • Image Analysis
  • Face Detection
  • Saliency Map
  • Evaluation


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