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» Learning to Rank with Supplementary Data
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142
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CIKM
2011
Springer
14 years 3 months ago
A probabilistic method for inferring preferences from clicks
Evaluating rankers using implicit feedback, such as clicks on documents in a result list, is an increasingly popular alternative to traditional evaluation methods based on explici...
Katja Hofmann, Shimon Whiteson, Maarten de Rijke
156
Voted
CVPR
2006
IEEE
16 years 5 months ago
Semi-Supervised Classification Using Linear Neighborhood Propagation
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...
151
Voted
KDD
2010
ACM
252views Data Mining» more  KDD 2010»
15 years 7 months ago
Fast query execution for retrieval models based on path-constrained random walks
Many recommendation and retrieval tasks can be represented as proximity queries on a labeled directed graph, with typed nodes representing documents, terms, and metadata, and labe...
Ni Lao, William W. Cohen
151
Voted
MLDM
2005
Springer
15 years 9 months ago
CorePhrase: Keyphrase Extraction for Document Clustering
Abstract. The ability to discover the topic of a large set of text documents using relevant keyphrases is usually regarded as a very tedious task if done by hand. Automatic keyphra...
Khaled M. Hammouda, Diego N. Matute, Mohamed S. Ka...
131
Voted
CIKM
2008
Springer
15 years 5 months ago
Mining conceptual graphs for knowledge acquisition
This work addresses the use of computational linguistic analysis techniques for conceptual graphs learning from unstructured texts. A technique including both content mining and i...
Milagros Fernández, Eric Villemonte de la C...