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» Listwise approach to learning to rank: theory and algorithm
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ICML
2005
IEEE
14 years 9 months ago
Augmenting naive Bayes for ranking
Naive Bayes is an effective and efficient learning algorithm in classification. In many applications, however, an accurate ranking of instances based on the class probability is m...
Harry Zhang, Liangxiao Jiang, Jiang Su
GCA
2009
13 years 6 months ago
A Learning Approach to Mechanism Design in Grid Resource Allocation
In this article a new algorithm for grid resource allocation based upon the theory of Algorithmic Mechanism Design (AMD) is presented. This algorithm is targeted at minimizing cost...
Mahmoud Moravej, Saeed Parsa
WWW
2011
ACM
13 years 4 months ago
Ranking in context-aware recommender systems
As context is acknowledged as an important factor that can affect users’ preferences, many researchers have worked on improving the quality of recommender systems by utilizing ...
Minsuk Kahng, Sangkeun Lee, Sang-goo Lee
WSDM
2009
ACM
104views Data Mining» more  WSDM 2009»
14 years 3 months ago
Top-k aggregation using intersections of ranked inputs
There has been considerable past work on efficiently computing top k objects by aggregating information from multiple ranked lists of these objects. An important instance of this...
Ravi Kumar, Kunal Punera, Torsten Suel, Sergei Vas...
WWW
2005
ACM
14 years 9 months ago
Object-level ranking: bringing order to Web objects
In contrast with the current Web search methods that essentially do document-level ranking and retrieval, we are exploring a new paradigm to enable Web search at the object level....
Zaiqing Nie, Yuanzhi Zhang, Ji-Rong Wen, Wei-Ying ...