Abstract
The MediaEval 2019 Task “Multimedia for Recommender Systems” investigates the potential of leveraging multimedia content to enhance recommender systems. In this task, participants use a wealth of information from text, images, and audio to predict the success of items. Thereby, we advance the state-of-the-art of content-based recommender systems by leveraging multimedia content.
Original language | English |
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Publication status | Published - 2019 |
Event | 2019 Working Notes of the MediaEval Workshop, MediaEval 2019 - Sophia Antipolis, France Duration: 27 Oct 2019 → 30 Oct 2019 |
Conference
Conference | 2019 Working Notes of the MediaEval Workshop, MediaEval 2019 |
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Country/Territory | France |
City | Sophia Antipolis |
Period | 27/10/2019 → 30/10/2019 |
Bibliographical note
Publisher Copyright:© 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
Keywords
- Audio
- Content-based filtering
- Feature engineering
- Images
- Movies
- Multimedia
- News
- Recommender systems
- Text
- Video
ASJC Scopus subject areas
- General Computer Science