Impedance coupling in content-targeted advertising
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Finding advertising keywords on web pages
Proceedings of the 15th international conference on World Wide Web
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Automated summarization of narrative video on a semantic level
ICSC '07 Proceedings of the International Conference on Semantic Computing
Advertising keyword suggestion based on concept hierarchy
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Finding keyword from online broadcasting content for targeted advertising
Proceedings of the 1st international workshop on Data mining and audience intelligence for advertising
Keyword extraction for contextual advertisement
Proceedings of the 17th international conference on World Wide Web
To swing or not to swing: learning when (not) to advertise
Proceedings of the 17th ACM conference on Information and knowledge management
Contextual video advertising system using scene information inferred from video scripts
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Interactive Web Video Advertising with Context Analysis and Search
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Practical Machine Learning Tools and Techniques
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The wide availability of online video content in the Internet has changed the way users interact with TV. In fact, TV users often watch the news, movies and TV series through the Web. Along with this change, new advertisement of products and services have emerged. The success of contextual advertising in the Web, mainly related to finding advertising keywords on page content, has motivated us to apply them to video. Textual evidence extracted from videos may provide good contextualization source for advertising. In this work, we evaluate the usefulness of movies scripts as a source of information for contextual advertising in video. We adopted a machine learning-based strategy to finding keywords and advertising. We studied not only features proven be useful in earlier studies, as well as novel features proposed and derived from the ad collection. We evaluate the impact of using scripts both in finding keywords and in finding relevant ads. The results indicate that the studies features were more useful for finding keywords than ads. Features derived from the ad collection performed consistently well in finding keywords. We also observed that the best keywords are found in the script section which describes the characters' actions and scenarios than in the one which describes the dialogues.