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83
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WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
15 years 7 months ago
Inferring Search Behaviors Using Partially Observable Markov (POM) Model
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
Kuansan Wang, Nikolas Gloy, Xiaolong Li
ICDM
2009
IEEE
155views Data Mining» more  ICDM 2009»
15 years 4 months ago
Stacked Gaussian Process Learning
—Triggered by a market relevant application that involves making joint predictions of pedestrian and public transit flows in urban areas, we address the question of how to utili...
Marion Neumann, Kristian Kersting, Zhao Xu, Daniel...
93
Voted
EMNLP
2007
14 years 11 months ago
Bootstrapping Information Extraction from Field Books
We present two machine learning approaches to information extraction from semi-structured documents that can be used if no annotated training data are available, but there does ex...
Sander Canisius, Caroline Sporleder
WOSP
2004
ACM
15 years 3 months ago
Analysing UML 2.0 activity diagrams in the software performance engineering process
In this paper we present an original method of analysing the newlyrevised UML2.0 activity diagrams. Our analysis method builds on our formal interpretation of these diagrams with ...
C. Canevet, Stephen Gilmore, Jane Hillston, Le&ium...
ICMLC
2005
Springer
15 years 3 months ago
Automatic 3D Motion Synthesis with Time-Striding Hidden Markov Model
In this paper we present a new method, time-striding hidden Markov model (TSHMM), to learn from long-term motion for atomic behaviors and the statistical dependencies among them. T...
Yi Wang, Zhi-Qiang Liu, Li-Zhu Zhou