TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Vocabulary Expansion Technique for Advertisement Classification |
| 영문제목(English Title) |
Vocabulary Expansion Technique for Advertisement Classification |
| 저자(Author) |
Jin-Yong Jung
Jung-Hyun Lee
JongWoo Ha
SangKeun Lee
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| 원문수록처(Citation) |
VOL 06 NO. 05 PP. 1373 ~ 1387 (2012. 05) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
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. |
| 키워드(Keyword) |
Advertisement classification
vocabulary expansion
semantic association
query log
centroid classifier
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| 파일첨부 |
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