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Can social features help learning to rank YouTube videos?

Chelaru, Sergiu Viorel
Orellana-Rodriguez, Claudia
Altıngövde, İsmail Sengör
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.