Categorization of display ads using image and landing page features
Andrew Kae, Kin Fai Kan, Vijay K. Narayanan, Dragomir Yankov · 2011
We consider the problem of automatically categorizing display ad images into a taxonomy of relevant interest categories. In particular, we focus on the efficacy of using image features extracted by OCR techniques from the ad images, in addition to the features from the text in the title, keywords and body of the landing page of the ad, and the features of the advertiser, in predicting the category of the display ad. An automated ad categorization tool has multiple uses in display advertising including increasing the ad categorization coverage, scaling up the ad categorization capacity to handle large volumes of ads by reducing the amount of human editorial effort and better utilizing the human editorial experts to focus on categorizing difficult ads. The ad image and landing page features extracted in this ad categorization system can also be used to improve the matching and ranking steps of ad selection algorithms in display ad serving systems.