Graph ambiguity

In this paper, we propose a rigorous way to define the concept of ambiguity in the domain of graphs. In past studies, the classical definition of ambiguity has been derived starting from fuzzy set and fuzzy information theories. Our aim is to show that also in the domain of the graphs it is possible to derive a formulation able to capture the same semantic and mathematical concept. To strengthen the theoretical results, we discuss the application of the graph ambiguity concept to the graph classification setting, conceiving a new kind of inexact graph matching procedure. The results prove that the graph ambiguity concept is a characterizing and discriminative property of graphs.

[1]  Vipin Kumar,et al.  Multilevel k-way hypergraph partitioning , 1999, DAC '99.

[2]  Bart Kosko,et al.  Fuzzy entropy and conditioning , 1986, Inf. Sci..

[3]  Santosh S. Vempala,et al.  On clusterings: Good, bad and spectral , 2004, JACM.

[4]  Xuelong Li,et al.  A survey of graph edit distance , 2010, Pattern Analysis and Applications.

[5]  Fakhri Karray,et al.  Fuzzy entropy: a brief survey , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[6]  Charu C. Aggarwal,et al.  Managing and Mining Graph Data , 2010, Managing and Mining Graph Data.

[7]  Robert P. W. Duin,et al.  The Dissimilarity Representation for Pattern Recognition - Foundations and Applications , 2005, Series in Machine Perception and Artificial Intelligence.

[8]  T. S. Evans,et al.  Complex networks , 2004 .

[9]  Hans Rademacher,et al.  On the Partition Function p(n) , 1938 .

[10]  V. Latora,et al.  Complex networks: Structure and dynamics , 2006 .

[11]  Chen Gang,et al.  Discussion on New Integral Entropy and Energy of Fuzzy Sets , 2009, 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery.

[12]  Chen Jianbin,et al.  A  Graph Partition-Based Soft Clustering Algorithm , 2008, 2008 Second International Symposium on Intelligent Information Technology Application.

[13]  Ken Ono,et al.  Algebraic formulas for the coefficients of half-integral weight harmonic weak Maass forms , 2011, 1104.1182.

[14]  Claudio Carpineto,et al.  Full-Subtopic Retrieval with Keyphrase-Based Search Results Clustering , 2009, 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology.

[15]  Antonello Rizzi,et al.  Automatic Classification of Graphs by Symbolic Histograms , 2007 .

[16]  Ulrik Brandes,et al.  Engineering graph clustering: Models and experimental evaluation , 2008, JEAL.

[17]  Alexander J. Smola,et al.  Learning with Kernels: support vector machines, regularization, optimization, and beyond , 2001, Adaptive computation and machine learning series.

[18]  R. A. Leibler,et al.  On Information and Sufficiency , 1951 .

[19]  Simon Parsons,et al.  Principles of Data Mining by David J. Hand, Heikki Mannila and Padhraic Smyth, MIT Press, 546 pp., £34.50, ISBN 0-262-08290-X , 2004, The Knowledge Engineering Review.

[20]  Lorenzo Livi,et al.  The graph matching problem , 2012, Pattern Analysis and Applications.

[21]  Ronald L. Rivest,et al.  Introduction to Algorithms , 1990 .

[22]  Kaspar Riesen,et al.  Graph Classification and Clustering Based on Vector Space Embedding , 2010, Series in Machine Perception and Artificial Intelligence.

[23]  R. Guimerà,et al.  Functional cartography of complex metabolic networks , 2005, Nature.

[24]  Klaus Obermayer,et al.  Structure Spaces , 2009, J. Mach. Learn. Res..

[25]  Lorenzo Livi,et al.  Graph Recognition by Seriation and Frequent Substructures Mining , 2012, ICPRAM.

[26]  Jiu-Lun Fan,et al.  Some new fuzzy entropy formulas , 2002, Fuzzy Sets Syst..

[27]  M. Aizerman,et al.  Theoretical Foundations of the Potential Function Method in Pattern Recognition Learning , 1964 .

[28]  Nello Cristianini,et al.  Kernel Methods for Pattern Analysis , 2003, ICTAI.

[29]  Lorenzo Livi,et al.  Inexact Graph Matching through Graph Coverage , 2012, ICPRAM.

[30]  Patrick J. F. Groenen,et al.  Modern Multidimensional Scaling: Theory and Applications , 2003 .

[31]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[32]  Ulrik Brandes,et al.  On Finding Graph Clusterings with Maximum Modularity , 2007, WG.

[33]  Nikhil R. Pal,et al.  Some new information measures for fuzzy sets , 1993, Inf. Sci..

[34]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[35]  Sankar K. Pal,et al.  Higher order fuzzy entropy and hybrid entropy of a set , 1992, Inf. Sci..

[36]  U. Brandes A faster algorithm for betweenness centrality , 2001 .

[37]  Zhongzhi Shi,et al.  Studies on Fuzzy Information Measures , 2007, FSKD.

[38]  A. Rizzi,et al.  Automatic Image Classification by a Granular Computing Approach , 2006, 2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing.

[39]  Bart Kosko,et al.  Addition as fuzzy mutual entropy , 1993, Inf. Sci..

[40]  Florian Dörfler,et al.  Kron Reduction of Graphs With Applications to Electrical Networks , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

[41]  G. Klir,et al.  ON MEASURES OF FUZZINESS AND FUZZY COMPLEMENTS , 1982 .

[42]  R. Yager ON THE MEASURE OF FUZZINESS AND NEGATION Part I: Membership in the Unit Interval , 1979 .

[43]  Xinbo Gao,et al.  HMM-based graph edit distance for image indexing , 2008 .

[44]  Eric P. Xing,et al.  Nonextensive Information Theoretic Kernels on Measures , 2009, J. Mach. Learn. Res..

[45]  D. S. Hooda,et al.  On generalized measures of fuzzy entropy , 2004 .

[46]  Padhraic Smyth,et al.  Algorithms for estimating relative importance in networks , 2003, KDD '03.

[47]  Settimo Termini,et al.  A Definition of a Nonprobabilistic Entropy in the Setting of Fuzzy Sets Theory , 1972, Inf. Control..

[48]  A. Kaufman,et al.  Introduction to the Theory of Fuzzy Subsets. , 1977 .

[49]  G. Hardy,et al.  Asymptotic Formulaæ in Combinatory Analysis , 1918 .

[50]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994 .

[51]  Michael Sipser,et al.  Introduction to the Theory of Computation , 1996, SIGA.

[52]  G. Klir Uncertainty and Information: Foundations of Generalized Information Theory , 2005 .

[53]  Jon Kleinberg,et al.  Authoritative sources in a hyperlinked environment , 1999, SODA '98.

[54]  An-Ping Zeng,et al.  Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph , 2004, Bioinform..

[55]  Jose C. Principe,et al.  Information Theoretic Learning - Renyi's Entropy and Kernel Perspectives , 2010, Information Theoretic Learning.

[56]  M. Zelen,et al.  Rethinking centrality: Methods and examples☆ , 1989 .

[57]  F. Chung Laplacians and the Cheeger Inequality for Directed Graphs , 2005 .

[58]  M. J. Frank,et al.  Associative Functions: Triangular Norms And Copulas , 2006 .

[59]  L. Zadeh Probability measures of Fuzzy events , 1968 .

[60]  Bernhard E. Boser,et al.  A training algorithm for optimal margin classifiers , 1992, COLT '92.

[61]  Meilin Wen,et al.  The entropy of fuzzy vectors , 2008, Comput. Math. Appl..

[62]  Xiu-Gang Shang,et al.  A note on fuzzy information measures , 1997, Pattern Recognit. Lett..

[63]  G. Karypis,et al.  Multi-Constraint Mesh Partitioning for Contact/Impact Computations , 2003, ACM/IEEE SC 2003 Conference (SC'03).

[64]  Mário A. T. Figueiredo,et al.  Generative Embeddings based on Rician Mixtures - Application to Kernel-based Discriminative Classification of Magnetic Resonance Images , 2012, ICPRAM.

[65]  S. V. N. Vishwanathan,et al.  Graph kernels , 2007 .

[66]  G. Rota The Number of Partitions of a Set , 1964 .

[67]  H. Sharp Cardinality of finite topologies , 1968 .

[68]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[69]  Hans-Peter Kriegel,et al.  Protein function prediction via graph kernels , 2005, ISMB.

[70]  Ulrik Brandes,et al.  Experiments on Graph Clustering Algorithms , 2003, ESA.

[71]  Horst Bunke,et al.  Bridging the Gap between Graph Edit Distance and Kernel Machines , 2007, Series in Machine Perception and Artificial Intelligence.

[72]  A. Rényi On Measures of Entropy and Information , 1961 .

[73]  Fan Chung,et al.  Spectral Graph Theory , 1996 .

[74]  W. Pedrycz,et al.  An introduction to fuzzy sets : analysis and design , 1998 .