Ranking news-quality multimedia

Research output: Chapter in Book/Report/Conference proceedingConference contribution


News editors need to find the photos that best illustrate a news piece and fulfill news-media quality standards, while being pressed to also find the most recent photos of live events. Recently, it became common to use social-media content in the context of news media for its unique value in terms of immediacy and quality. Consequently, the amount of images to be considered and filtered through is now too much to be handled by a person. To aid the news editor in this process, we propose a framework designed to deliver high-quality, news-press type photos to the user. The framework, composed of two parts, is based on a ranking algorithm tuned to rank professional media highly and a visual SPAM detection module designed to filter-out low-quality media. The core ranking algorithm is leveraged by aesthetic, social and deep-learning semantic features. Evaluation showed that the proposed framework is effective at finding high-quality photos (true-positive rate) achieving a retrieval MAP of 64.5% and a classification precision of 70%.

Original languageEnglish
Title of host publicationICMR 2018 - Proceedings of the 2018 ACM International Conference on Multimedia Retrieval
PublisherAssociation for Computing Machinery, Inc
Number of pages9
ISBN (Print)9781450350464
Publication statusPublished - 5 Jun 2018
Event8th ACM International Conference on Multimedia Retrieval, ICMR 2018 - Yokohama, Japan
Duration: 11 Jun 201814 Jun 2018


Conference8th ACM International Conference on Multimedia Retrieval, ICMR 2018


  • News photos
  • News quality
  • Social-media
  • Visual aesthetics

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