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Can Social Features Help Learning to Rank YouTube Videos?

  • Conference paper
Web Information Systems Engineering - WISE 2012 (WISE 2012)

Abstract

We investigate the impact of social features (such as likes, dislikes, comments, etc.) on the effectiveness of video retrieval in YouTube video sharing system using state-of-the-art learning to rank approaches and a greedy feature selection algorithm. Our experiments based on a dataset of 3,500 annotated query-video pairs reveal that social features are promising to improve the retrieval performance.

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Chelaru, S.V., Orellana-Rodriguez, C., Altingovde, I.S. (2012). Can Social Features Help Learning to Rank YouTube Videos?. In: Wang, X.S., Cruz, I., Delis, A., Huang, G. (eds) Web Information Systems Engineering - WISE 2012. WISE 2012. Lecture Notes in Computer Science, vol 7651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35063-4_40

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  • DOI: https://doi.org/10.1007/978-3-642-35063-4_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35062-7

  • Online ISBN: 978-3-642-35063-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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