Name
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% similar to 9.7% improvements in terms of the hierarchical f-measure over the baseline classifiers without vocabulary expansion. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.3837/tiis.2012.05.007 | KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS |
Keywords | Field | DocType |
Advertisement classification,vocabulary expansion,semantic association,query log,centroid classifier | Web search query,Contextual advertising,Web page,Information retrieval,Semantic association,Computer science,Web query classification,Service provider,Vocabulary | Journal |
Volume | Issue | ISSN |
6 | 5 | 1976-7277 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinyong Jung | 1 | 113 | 7.70 |
| Jung-Hyun Lee | 2 | 188 | 23.59 |
| JongWoo Ha | 3 | 55 | 6.79 |
| Sangkeun Lee | 4 | 498 | 65.59 |