A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Properties of Embedding Methods for Similarity Searching in Metric Spaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Cluster Preserving Embedding of Nonmetric Proximity Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Pattern Vectors from Algebraic Graph Theory
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Dissimilarity Representation for Pattern Recognition: Foundations And Applications (Machine Perception and Artificial Intelligence)
Prototype selection for dissimilarity-based classifiers
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
Feature selection for graph-based image classifiers
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
A graph matching based approach to fingerprint classification using directional variance
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Recursive processing of cyclic graphs
IEEE Transactions on Neural Networks
Reducing the Dimensionality of Vector Space Embeddings of Graphs
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Kernel k-Means Clustering Applied to Vector Space Embeddings of Graphs
ANNPR '08 Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition
Exact Median Graph Computation Via Graph Embedding
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Graph Classification Based on Dissimilarity Space Embedding
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Reducing the dimensionality of dissimilarity space embedding graph kernels
Engineering Applications of Artificial Intelligence
Approximate graph edit distance computation by means of bipartite graph matching
Image and Vision Computing
A Recursive Embedding Approach to Median Graph Computation
GbRPR '09 Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition
Dissimilarity Based Vector Space Embedding of Graphs Using Prototype Reduction Schemes
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Finding the k-Most Abnormal Subgraphs from a Single Graph
DS '09 Proceedings of the 12th International Conference on Discovery Science
A family of novel graph kernels for structural pattern recognition
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
A comparison between two representatives of a set of graphs: median vs. barycenter graph
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Indexing tree and subtree by using a structure network
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Graph embedding for pattern recognition
ICPR'10 Proceedings of the 20th International conference on Recognizing patterns in signals, speech, images, and videos
Graph embedding using constant shift embedding
ICPR'10 Proceedings of the 20th International conference on Recognizing patterns in signals, speech, images, and videos
Entropy versus heterogeneity for graphs
GbRPR'11 Proceedings of the 8th international conference on Graph-based representations in pattern recognition
Characterizing graphs using approximate von Neumann entropy
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Automatic human action recognition in videos by graph embedding
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
The dissimilarity space: Bridging structural and statistical pattern recognition
Pattern Recognition Letters
A new protein graph model for function prediction
Computational Biology and Chemistry
Hypergraph-based image retrieval for graph-based representation
Pattern Recognition
Similarity-Based Retrieval With Structure-Sensitive Sparse Binary Distributed Representations
Computational Intelligence
Arabic handwriting recognition using structural and syntactic pattern attributes
Pattern Recognition
Graph characterizations from von Neumann entropy
Pattern Recognition Letters
Two new graphs kernels in chemoinformatics
Pattern Recognition Letters
On graph-associated matrices and their eigenvalues for optical character recognition
ANNPR'12 Proceedings of the 5th INNS IAPR TC 3 GIRPR conference on Artificial Neural Networks in Pattern Recognition
Top-k Similar Graph Matching Using TraM in Biological Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Human action recognition in video by fusion of structural and spatio-temporal features
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Discriminative prototype selection methods for graph embedding
Pattern Recognition
On the informativeness of asymmetric dissimilarities
SIMBAD'13 Proceedings of the Second international conference on Similarity-Based Pattern Recognition
A new proposal for graph classification using frequent geometric subgraphs
Data & Knowledge Engineering
Spectral graph features for the classification of graphs and graph sequences
Computational Statistics
| Hi-index | 0.00 |
The field of statistical pattern recognition is characterized by the use of feature vectors for pattern representation, while strings or, more generally, graphs are prevailing in structural pattern recognition. In this paper we aim at bridging the gap between the domain of feature based and graph based object representation. We propose a general approach for transforming graphs into n-dimensional real vector spaces by means of prototype selection and graph edit distance computation. This method establishes the access to the wide range of procedures based on feature vectors without loosing the representational power of graphs. Through various experimental results we show that the proposed method, using graph embedding and classification in a vector space, outperforms the tradional approach based on k-nearest neighbor classification in the graph domain.