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» Information Theory, Inference, and Learning Algorithms
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WSDM
2012
ACM
285views Data Mining» more  WSDM 2012»
12 years 3 months ago
Probabilistic models for personalizing web search
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
MANSCI
2007
90views more  MANSCI 2007»
13 years 7 months ago
Selecting a Selection Procedure
Selection procedures are used in a variety of applications to select the best of a finite set of alternatives. ‘Best’ is defined with respect to the largest mean, but the me...
Jürgen Branke, Stephen E. Chick, Christian Sc...
TREC
2004
13 years 9 months ago
Can We Get A Better Retrieval Function From Machine?
The quality of an information retrieval system heavily depends on its retrieval function, which returns a similarity measurement between the query and each document in the collect...
Weiguo Fan, Wensi Xi, Edward A. Fox, Li Wang
MOBICOM
2006
ACM
14 years 1 months ago
Analysis and implications of student contact patterns derived from campus schedules
Characterizing mobility or contact patterns in a campus environment is of interest for a variety of reasons. Existing studies of these patterns can be classified into two basic a...
Vikram Srinivasan, Mehul Motani, Wei Tsang Ooi
KDD
2006
ACM
115views Data Mining» more  KDD 2006»
14 years 8 months ago
Supervised probabilistic principal component analysis
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...