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» Learning Semantic Categories from Clickthrough Logs
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KDD
2009
ACM
232views Data Mining» more  KDD 2009»
15 years 4 months ago
Probabilistic latent semantic user segmentation for behavioral targeted advertising
Behavioral Targeting (BT), which aims to deliver the most appropriate advertisements to the most appropriate users, is attracting much attention in online advertising market. A ke...
Xiaohui Wu, Jun Yan, Ning Liu, Shuicheng Yan, Ying...
ECAI
2008
Springer
15 years 1 months ago
Extracting Semantic Annotations from Moodle Data
The purpose of this paper is to provide a solution which allows automatic reasoning processes over Moodle activities logs, in order to obtain user-personalized recommendations. Act...
Mihai Gabroveanu, Ion-Mircea Diaconescu
NAACL
2010
14 years 9 months ago
Learning Dense Models of Query Similarity from User Click Logs
The goal of this work is to integrate query similarity metrics as features into a dense model that can be trained on large amounts of query log data, in order to rank query rewrit...
Fabio De Bona, Stefan Riezler, Keith Hall, Massimi...
WWW
2008
ACM
16 years 8 days ago
Asymmetrical query recommendation method based on bipartite network resource allocation
This paper presents a new query recommendation method that generates recommended query list by mining large-scale user logs. Starting from the user logs of click-through data, we ...
Zhiyuan Liu, Maosong Sun
CVIU
2008
209views more  CVIU 2008»
14 years 11 months ago
Combining visual dictionary, kernel-based similarity and learning strategy for image category retrieval
This paper presents a search engine architecture, RETIN, aiming at retrieving complex categories in large image databases. For indexing, a scheme based on a two-step quantization ...
Philippe Henri Gosselin, Matthieu Cord, Sylvie Phi...