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AdKDD@KDD 2009: Paris, France
- Ying Li, Arun C. Surendran, Dou Shen:
Proceedings of the 3rd ACM SIGKDD Workshop on Data Mining and Audience Intelligence for Advertising, Paris, France, June 28, 2009. ACM 2009, ISBN 978-1-60558-671-7 - Foster J. Provost:
Brand advertising, on-line audiences, and social media: invited talk. - Ting Li, Ning Liu, Jun Yan, Gang Wang, Fengshan Bai, Zheng Chen:
A Markov chain model for integrating behavioral targeting into contextual advertising. 1-9 - Xiaohui Wu, Jun Yan, Ning Liu, Shuicheng Yan, Ying Chen, Zheng Chen:
Probabilistic latent semantic user segmentation for behavioral targeted advertising. 10-17 - Xin-Jing Wang, Mo Yu, Lei Zhang, Rui Cai, Wei-Ying Ma:
Argo: intelligent advertising by mining a user's interest from his photo collections. 18-26 - Anton Schwaighofer, Joaquin Quiñonero Candela, Thomas Borchert, Thore Graepel, Ralf Herbrich:
Scalable clustering and keyword suggestion for online advertisements. 27-36 - Luís Sarmento, Paulo Trezentos, João Pedro Gonçalves, Eugénio C. Oliveira
:
Inferring local synonyms for improving keyword suggestion in an on-line advertisement system. 37-45 - Benyah Shaparenko, Özgür Çetin, Rukmini Iyer:
Data-driven text features for sponsored search click prediction. 46-54 - Yunzhang Zhu, Gang Wang, Junli Yang, Dakan Wang, Jun Yan, Zheng Chen:
Revenue optimization with relevance constraint in sponsored search. 55-60 - Adam Isaac Juda, S. Muthukrishnan, Ashish Rastogi:
Pricing guidance in ad sale negotiations: the PrintAds example. 61-68 - Saeed Alaei
, Esteban Arcaute, Samir Khuller, Wenjing Ma, Azarakhsh Malekian, John A. Tomlin:
Online allocation of display advertisements subject to advanced sales contracts. 69-77 - Michael May, Christine Körner, Dirk Hecker
, Martial Pasquier
, Urs Hofmann, Felix Mende:
Handling missing values in GPS surveys using survival analysis: a GPS case study of outdoor advertising. 78-84 - Yannet Interian, Sundar Dorai-Raj, Igor Naverniouk, P. J. Opalinski, Kaustuv, Dan Zigmond:
Ad quality on TV: predicting television audience retention. 85-91

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