Unsupervised learning by probabilistic latent semantic analysis
Machine Learning
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Finding advertising keywords on web pages
Proceedings of the 15th international conference on World Wide Web
To search or to label?: predicting the performance of search-based automatic image classifiers
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Demographic prediction based on user's browsing behavior
Proceedings of the 16th international conference on World Wide Web
A note on Platt's probabilistic outputs for support vector machines
Machine Learning
vADeo: video advertising system
Proceedings of the 15th international conference on Multimedia
(Un)Reliability of video concept detection
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Contextual in-image advertising
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Learning tag relevance by neighbor voting for social image retrieval
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
How much can behavioral targeting help online advertising?
Proceedings of the 18th international conference on World wide web
Foundations and Trends in Information Retrieval
Argo: intelligent advertising by mining a user's interest from his photo collections
Proceedings of the Third International Workshop on Data Mining and Audience Intelligence for Advertising
Video2Text: Learning to Annotate Video Content
ICDMW '09 Proceedings of the 2009 IEEE International Conference on Data Mining Workshops
TubeTagger - YouTube-based Concept Detection
ICDMW '09 Proceedings of the 2009 IEEE International Conference on Data Mining Workshops
VideoSense: a contextual in-video advertising system
IEEE Transactions on Circuits and Systems for Video Technology
The Pascal Visual Object Classes (VOC) Challenge
International Journal of Computer Vision
Content-Based Methods for Predicting Web-Site Demographic Attributes
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Large scale evaluations of multimedia information retrieval: the TRECVid experience
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Dynamic vocabularies for web-based concept detection by trend discovery
Proceedings of the 20th ACM international conference on Multimedia
User demographics prediction based on mobile data
Pervasive and Mobile Computing
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The estimation of demographic target groups for web videos -- with applications in ad targeting -- poses a challenging problem, as the textual description and view statistics available for many clips is extremely sparse. Therefore, the goal of this paper is to link a clip's popularity across different viewer ages and genders on the one hand with the video content on the other: Employing user comments and user profiles on YouTube, we show that there is a strong correlation between demographic target groups and semantic concepts appearing in the video (like "teenage male" and "skateboarding"). Based on this observation, we suggest two approaches: First, the demographic target group of a clip is predicted automatically via a content-based concept detection. Second, should sufficient view statistics already give a good impression of a video's audience, we show that this information can serve as a valuable additional signal to disambiguate concept detection. Our experimental results on a dataset of 14,000 YouTube clips commented by 1 mio. users show that -- though content-based viewership estimation is a challenging problem -- suitable demographic groups can be suggested by concept detection. Also, a combination with demographic information as an additional signal leads to relative improvements of concept detection accuracy by 47%.