• Corpus ID: 18217098

Click-Through Prediction for Sponsored Search Advertising with Hybrid Models

@inproceedings{Wang2012ClickThroughPF,
  title={Click-Through Prediction for Sponsored Search Advertising with Hybrid Models},
  author={Xingxing Wang and Shijie Lin and Dongying Kong and Liheng Xu and Qiang Yan and Siwei Lai and Liang Wu and Alvin Chin and Guibo Zhu and Heng Gao and Yang Wu and Danny Bickson and Yuanfeng Du and Neng Gong and Chengchun Shu and Shuang Wang and Kang Liu and Shuren Li and Jun Zhao and Fei Tan and Yuanchun Zhou},
  year={2012}
}
In this paper, we report our approach of KDD Cup 2012 track 2 to predicting the click-through rate (CTR) of advertisements. To accurately predict the CTR of an ad is important for commercial search engine companies for deciding the click prices and the order of impressions. We first implemented three existing methods including Online Bayesian Probit Regression (BPR), Support Vector Machine (SVM) and Latent Factor Model (LFM). In order to fully exploit the training set, several Maximum… 

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