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ICDM
2007
IEEE
175views Data Mining» more  ICDM 2007»
16 years 25 days ago
gApprox: Mining Frequent Approximate Patterns from a Massive Network
Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, deman...
Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han
DOLAP
2006
ACM
16 years 14 days ago
HYPE: mining hierarchical sequential patterns
Mining data warehouses is still an open problem as few approaches really take the specificities of this framework into account (e.g. multidimensionality, hierarchies, historized ...
Marc Plantevit, Anne Laurent, Maguelonne Teisseire
ICRA
2002
IEEE
114views Robotics» more  ICRA 2002»
15 years 11 months ago
Learning Motion Patterns of Persons for Mobile Service Robots
We propose a method for learning models of people’s motion behaviors in an indoor environment. As people move through their environments, they do not move randomly. Instead, the...
Maren Bennewitz, Wolfram Burgard, Sebastian Thrun
AAAI
2010
15 years 8 months ago
A Bayesian Nonparametric Approach to Modeling Mobility Patterns
Constructing models of mobile agents can be difficult without domain-specific knowledge. Parametric models flexible enough to capture all mobility patterns that an expert believes...
Joshua Mason Joseph, Finale Doshi-Velez, Nicholas ...
ICGA
2007
157views Optimization» more  ICGA 2007»
15 years 6 months ago
Computing "Elo Ratings" of Move Patterns in the Game of Go
Abstract. Move patterns are an essential method to incorporate domain knowledge into Go-playing programs. This paper presents a new Bayesian technique for supervised learning of su...
Rémi Coulom