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On Graph Kernels: Hardness Results and Efficient Alternatives
TLDR
We propose a generalized family of graph kernels based on walks which includes the kernels proposed in [4] as special cases while still being polynomially computable. Expand
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An Algorithm for Multi-relational Discovery of Subgroups
TLDR
We consider the problem of finding statistically unusual subgroups in a multi-relation database, and extend previous work on single-relation subgroup discovery. Expand
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Geovisual analytics for spatial decision support: Setting the research agenda
TLDR
This article summarizes the results of the workshop on Visualization, Analytics & Spatial Decision Support, which took place at the GIScience conference in September 2006. Expand
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Visual analytics tools for analysis of movement data
TLDR
By combining interactive visual displays, which are essential for supporting human perception, cognition, and reasoning, with database operations and computational methods, it is possible to effectively support human analysts in understanding movement behaviors and mobility patterns. Expand
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Cyclic pattern kernels for predictive graph mining
TLDR
In this paper, we show that with a natural set of patterns, cyclic and tree patterns, it is possible to eliminate the restriction to frequent patterns. Expand
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A conceptual framework and taxonomy of techniques for analyzing movement
TLDR
We present a conceptual framework that describes in a systematic and comprehensive way the possible types of information that can be extracted from movement data and on this basis defines the respective types of analytical tasks. Expand
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Proceedings of the 22nd international conference on Machine learning
TLDR
This volume, which is also available online from http://www.machinelearning.org, contains the papers accepted for presentation at ICML-2005, the 22nd lnternational Conference on Machine Learning, which was held at the University of Bonn in Germany from August 7 to August 11, 2005. Expand
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Active Hidden Markov Models for Information Extraction
TLDR
We develop an active hidden Markov model that selects unlabeled tokens and asks the user to label them. Expand
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Transformation-Based Learning Using Multirelational Aggregation
TLDR
We build on popular transformation-based approaches to ILP and describe how they can naturally be extended with relational aggregation. Expand
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Tight Optimistic Estimates for Fast Subgroup Discovery
TLDR
We present tight optimistic estimates for the most popular binary and multi-class quality functions, and present a family of increasingly efficient approximations to these optimal functions. Expand
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