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EMNLP
2009
13 years 2 months ago
Empirical Exploitation of Click Data for Task Specific Ranking
There have been increasing needs for task specific rankings in web search such as rankings for specific query segments like long queries, time-sensitive queries, navigational quer...
Anlei Dong, Yi Chang, Shihao Ji, Ciya Liao, Xin Li...
WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
14 years 2 months ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
KDD
2010
ACM
289views Data Mining» more  KDD 2010»
13 years 2 months ago
Exploitation and exploration in a performance based contextual advertising system
The dynamic marketplace in online advertising calls for ranking systems that are optimized to consistently promote and capitalize better performing ads. The streaming nature of on...
Wei Li 0010, Xuerui Wang, Ruofei Zhang, Ying Cui, ...
AAAI
2008
13 years 7 months ago
Zero-data Learning of New Tasks
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
Hugo Larochelle, Dumitru Erhan, Yoshua Bengio
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
14 years 5 months ago
Learning optimal ranking with tensor factorization for tag recommendation
Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
Steffen Rendle, Leandro Balby Marinho, Alexandros ...