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Automatic Keywords Generation for Contextual Advertising by Pengqi Liu; Javad Azimi; Ruofei Zhang is a scholarly article available to read on EtoBox.

What is Automatic Keywords Generation for Contextual Advertising about?

Contextual Advertising (CA) is an important area in the industry of online advertising. Typically, CA algorithms return a set of related ads based on some keywords extracted from the content of webpages. Therefore, extracting the best set of representative keywords from a given webpage is the key to the success of CA. In this paper, we introduce a new keywords generation approach that uses some novel NLP features including POS and named-entities tagging. Unlike most of the existing keyword extraction algorithms, our proposed framework is able to generate some related keywords which do not exist in the webpage. A monetization parameter, predicted from historical search keyword performance, is also used to rank potential keywords in order to balance the RPM (Revenue Per 1000 Matches) and relevance. Experimental results over a very large real-world data set shows that the proposed approach can outperform the state-of-theart system in both relevance and monetization metrics.

Author

Pengqi Liu; Javad Azimi; Ruofei Zhang

Publisher

ACM

Published

2014

Language

EN