ML92 Proceedings of the ninth international workshop on Machine learning
Mining patterns from graph traversals
Data & Knowledge Engineering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Molecular Fragments: Finding Relevant Substructures of Molecules
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Discovering Frequent Geometric Subgraphs
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
A quickstart in frequent structure mining can make a difference
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Frequent Substructure-Based Approaches for Classifying Chemical Compounds
IEEE Transactions on Knowledge and Data Engineering
The Dissimilarity Representation for Pattern Recognition: Foundations And Applications (Machine Perception and Artificial Intelligence)
Prototype selection for dissimilarity-based classifiers
Pattern Recognition
Discovering frequent geometric subgraphs
Information Systems
Mining Frequent Connected Subgraphs Reducing the Number of Candidates
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
IAM Graph Database Repository for Graph Based Pattern Recognition and Machine Learning
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Frequent Subgraph Retrieval in Geometric Graph Databases
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Graph nodes clustering with the sigmoid commute-time kernel: A comparative study
Data & Knowledge Engineering
Mining globally distributed frequent subgraphs in a single labeled graph
Data & Knowledge Engineering
Text classification using graph mining-based feature extraction
Knowledge-Based Systems
Corpus callosum MR image classification
Knowledge-Based Systems
Graph embedding in vector spaces by means of prototype selection
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
Time and space efficient discovery of maximal geometric graphs
DS'07 Proceedings of the 10th international conference on Discovery science
ACONS: a new algorithm for clustering documents
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Full duplicate candidate pruning for frequent connected subgraph mining
Integrated Computer-Aided Engineering
Approximate weighted frequent pattern mining with/without noisy environments
Knowledge-Based Systems
Image Classification Using Subgraph Histogram Representation
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Transforming strings to vector spaces using prototype selection
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
An efficient graph-mining method for complicated and noisy data with real-world applications
Knowledge and Information Systems - Special Issue on "Context-Aware Data Mining (CADM)"
Frequent approximate subgraphs as features for graph-based image classification
Knowledge-Based Systems
Towards the unification of structural and statistical pattern recognition
Pattern Recognition Letters
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Geometric graph mining has been identified as a need in many applications. This technique detects recurrent patterns in data taking into account some geometric distortions. To meet this need, some graph miners have been developed for detecting frequent geometric subgraphs. However, there are few works that attend to actually apply this kind of pattern as feature for classification tasks. In this paper, a new geometric graph miner and a framework, for using frequent geometric subgraphs in classification, are proposed. Our solution was tested in the already reported AIDS database. The experimentation shows that our proposal gets better results than graph-based classification using non-geometric graph miners.