Name
Abstract | ||
|---|---|---|
Contextual advertising seeks to place relevant ads to generic web pages based on their contents. Recently, it has been observed that classifying web pages into a well-organized taxonomy of topics is promising for matching topically relevant ads to web pages. Following the observation, in this paper we propose two methods to increase classification accuracy for web pages in the context of contextual advertising. Our strategy is to enhance the baseline classifier by reflecting unique features of web pages and the taxonomy. In particular, category tags extracted from web pages are utilized to augment term weights, and the hierarchical structure of the taxonomy is taken into account to categorize web pages with high confidence. We conduct a series of experiments to evaluate the proposed methods, and the results show that classification accuracy is increased up to 11% compared to the baseline classifier. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1651587.1651598 | WIDM |
Keywords | Field | DocType |
topically relevant ad,baseline classifier,contextual advertising,web page,generic web page,novel web page classification,well-organized taxonomy,classifying web page,classification accuracy,category tag,relevant ad,web pages | Data mining,Categorization,Contextual advertising,Web page,Information retrieval,Computer science,Website Parse Template,Web query classification,Social Semantic Web,Classifier (linguistics),Concept hierarchy | Conference |
Citations | PageRank | References |
4 | 0.44 | 16 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jung-Jin Lee | 1 | 89 | 4.29 |
| Jung-Hyun Lee | 2 | 188 | 23.59 |
| JongWoo Ha | 3 | 55 | 6.79 |
| Sangkeun Lee | 4 | 498 | 65.59 |