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Data Set Information: This dataset represents a set of possible advertisements on Internet pages. The features encode the geometry of the image (if available) as well as phrases occuring in the URL, the image's URL and alt text, the anchor text, and words occuring near the anchor text. The task is to predict whether an image is an advertisement ("ad") or not ("nonad"). Attribute Information: (3 continous; others binary; this is the "STANDARD encoding" mentioned in the [Kushmerick, 99].)
Relevant Papers: N. Kushmerick (1999). "Learning to remove Internet advertisements", 3rd Int Conf Autonomous Agents. Available at www.cs.ucd.ie/staff/nick/research/[Web Link].
Papers That Cite This Data Set1: ![]() Dmitriy Fradkin and David Madigan. Experiments with random projections for machine learning. KDD. 2003. [View Context]. Citation Request: Please refer to the Machine Learning Repository's citation policy |
[1] Papers were automatically harvested and associated with this data set, in collaboration with Rexa.info
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