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Alice's worlds of wonder: exploiting tags to understand images in terms of size and scale.

, , and . ACM Multimedia, page 643-646. ACM, (2011)

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Intent-Aware Video Search Result Optimization., , and . IEEE Trans. Multim., 16 (5): 1421-1433 (2014)User Intent in Multimedia Search: A Survey of the State of the Art and Future Challenges., , and . ACM Comput. Surv., 49 (2): 36:1-36:37 (2016)How 'How' Reflects What's What: Content-based Exploitation of How Users Frame Social Images., , , and . ACM Multimedia, page 397-406. ACM, (2014)Uploader Intent for Online Video: Typology, Inference, and Applications., , , , , and . IEEE Trans. Multim., 17 (8): 1200-1212 (2015)Search Personalization at Netflix., , , , and . WWW (Companion Volume), page 756-758. ACM, (2023)Reading between the tags to predict real-world size-class for visually depicted objects in images., , and . ACM Multimedia, page 273-282. ACM, (2011)A peer's-eye view: network term clouds in a peer-to-peer system., , , and . CIKM, page 1909-1912. ACM, (2011)When video search goes wrong: predicting query failure using search engine logs and visual search results., , , , , and . ACM Multimedia, page 319-328. ACM, (2012)SocialZap: Catch-up on Interesting Television Fragments Discovered from Social Media., , , , , , , , , and . ICMR, page 538. ACM, (2014)Overview of MediaEval 2011 Rich Speech Retrieval Task and Genre Tagging Task., , , , , and . MediaEval, volume 807 of CEUR Workshop Proceedings, CEUR-WS.org, (2011)