• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Vocabulary Expansion Technique for Advertisement Classification


Contextual advertising is an important revenue source for major service providers on the Web. Ads classification is one of main tasks in contextual advertising, and it is used to retrieve semantically relevant ads with respect to the content of web pages. However, it is difficult for traditional text classification methods to achieve satisfactory performance in ads classification due to scarce term features in ads. In this paper, we propose a novel ads classification method that handles the lack of term features for classifying ads with short text. The proposed method utilizes a vocabulary expansion technique using semantic associations among terms learned from large-scale search query logs. The evaluation results show that our methodology achieves 4.0% ‾ 9.7% improvements in terms of the hierarchical f-measure over the baseline classifiers without vocabulary expansion.


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Cite this article

[IEEE Style]
J. Jung, J. Lee, J. Ha and S. Lee, "Vocabulary Expansion Technique for Advertisement Classification," KSII Transactions on Internet and Information Systems, vol. 6, no. 5, pp. 1373-1387, 2012. DOI: 10.3837/tiis.2012.05.007.

[ACM Style]
Jin-Yong Jung, Jung-Hyun Lee, JongWoo Ha, and SangKeun Lee. 2012. Vocabulary Expansion Technique for Advertisement Classification. KSII Transactions on Internet and Information Systems, 6, 5, (2012), 1373-1387. DOI: 10.3837/tiis.2012.05.007.

[BibTeX Style]
@article{tiis:20126, title="Vocabulary Expansion Technique for Advertisement Classification", author="Jin-Yong Jung and Jung-Hyun Lee and JongWoo Ha and SangKeun Lee and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2012.05.007}, volume={6}, number={5}, year="2012", month={May}, pages={1373-1387}}