Publications

Josephine Thomas, Alice Moallemy-Oureh, Silvia Beddar-Wiesing, und Clara Holzhüter. Graph Neural Networks Designed for Different Graph Types: A Survey. Transactions on Machine Learning Research, 2023. [PUMA: imported itegpub isac-www graph graph_type graph_neural_network] URL

Bernardo Pereira Nunes, Ricardo Kawase, Stefan Dietze, Davide Taibi, Marco Antonio Casanova, und Wolfgang Nejdl. Can Entities be Friends?. In Giuseppe Rizzo, Pablo Mendes, Eric Charton, Sebastian Hellmann, und Aditya Kalyanpur (Hrsg.), Proceedings of the Web of Linked Entities Workshop in conjuction with the 11th International Semantic Web Conference, (906):45--57, November 2012. [PUMA: data detection entity graph linked relation web] URL

Denis Krompass, Maximilian Nickel, und Volker Tresp. Large-scale factorization of type-constrained multi-relational data. International Conference on Data Science and Advanced Analytics, DSAA 2014, Shanghai, China, October 30 - November 1, 2014, 18--24, IEEE, 2014. [PUMA: graph knowledge learning toread] URL

Klaus Heidtmann. Internet-Graphen. Informatik-Spektrum, (36)5:440-448, Springer Berlin Heidelberg, 2013. [PUMA: Graph Graphen Informatik Informatik-Spektrum Internet Spektrum graphs] URL

Svante Janson, Tomasz Luczak, und Andrzej Rucinski. Theory of random graphs. John Wiley & Sons, New York; Chichester, 2000. [PUMA: density graph random] URL

Reinhard Diestel. Graph Theory. I-XVI, 1-344, Springer-Verlag Heidelberg, New York, 2005. [PUMA: book density diesel graph theory] URL

Nikolas Landia, Stephan Doerfel, Robert Jäschke, Sarabjot Singh Anand, Andreas Hotho, und Nathan Griffiths. Deeper Into the Folksonomy Graph: FolkRank Adaptations and Extensions for Improved Tag Recommendations. cs.IR, (1310.1498)2013. [PUMA: 2013 bookmarking collaborative folkrank folksonomy graph iteg itegpub l3s recommender social tagging] URL

Stephan Doerfel, und Robert Jäschke. An analysis of tag-recommender evaluation procedures. Proceedings of the 7th ACM conference on Recommender systems, 343--346, ACM, New York, NY, USA, 2013. [PUMA: 2013 bibsonomy bookmarking collaborative core evaluation folkrank folksonomy graph iteg itegpub l3s recommender social tagging] URL

Nikolas Landia, Stephan Doerfel, Robert Jäschke, Sarabjot Singh Anand, Andreas Hotho, und Nathan Griffiths. Deeper Into the Folksonomy Graph: FolkRank Adaptations and Extensions for Improved Tag Recommendations. cs.IR, (1310.1498)2013. [PUMA: 2013 bookmarking collaborative folkrank folksonomy graph myown] URL

Nikolas Landia, Stephan Doerfel, Robert Jäschke, Sarabjot Singh Anand, Andreas Hotho, und Nathan Griffiths. Deeper Into the Folksonomy Graph: FolkRank Adaptations and Extensions for Improved Tag Recommendations. cs.IR, (1310.1498)2013. [PUMA: 2013 bookmarking collaborative folkrank folksonomy graph myown recommender social tagging] URL

Johan Ugander, Brian Karrer, Lars Backstrom, und Cameron Marlow. The Anatomy of the Facebook Social Graph. 2011. [PUMA: facebook graph network social] URL

Michael Baur, Marco Gaertler, Robert Görke, Marcus Krug, und Dorothea Wagner. Generating Graphs with Predefined k-Core Structure. Proceedings of the European Conference of Complex Systems, Oktober 2007. [PUMA: analysis core generator graph structure] URL

Xiaozhong Liu, Jinsong Zhang, und Chun Guo. Full-Text Citation Analysis: A New Method to Enhance Scholarly Network. Journal of the American Society for Information Science and Technology, 2012. [PUMA: analysis citation classification graph pagerank ranking scientometrics sota] URL

Xiaozhong Liu, Jinsong Zhang, und Chun Guo. Full-Text Citation Analysis: A New Method to Enhance Scholarly Network. Journal of the American Society for Information Science and Technology, 2012. [PUMA: analysis citation classification graph pagerank ranking scientometrics sota topic] URL

Torsten Zesch, und Iryna Gurevych. Analysis of the Wikipedia Category Graph for NLP Applications. Proceedings of the TextGraphs-2 Workshop (NAACL-HLT), 1--8, Association for Computational Linguistics, Rochester, April 2007. [PUMA: analysis category graph language natural network nlp processing wikipedia] URL

Bernardo Pereira Nunes, Ricardo Kawase, Stefan Dietze, Davide Taibi, Marco Antonio Casanova, und Wolfgang Nejdl. Can Entities be Friends?. In Giuseppe Rizzo, Pablo Mendes, Eric Charton, Sebastian Hellmann, und Aditya Kalyanpur (Hrsg.), Proceedings of the Web of Linked Entities Workshop in conjuction with the 11th International Semantic Web Conference, (906):45--57, November 2012. [PUMA: data detection entity graph linked relation web] URL

Vladimir Batagelj, und Matjaž Zaveršnik. Fast algorithms for determining (generalized) core groups in social networks. Advances in Data Analysis and Classification, (5)2:129-145, Springer, Berlin / Heidelberg, 2011. [PUMA: core graph] URL

Vladimir Batagelj, Andrej Mrvar, und Matjaž Zaveršnik. Partitioning Approach to Visualization of Large Graphs. In Jan Kratochvíyl (Hrsg.), Graph Drawing, (1731):90-97, Springer, Berlin / Heidelberg, 1999. [PUMA: core graph] URL

V. Batagelj, und M. Zaversnik. An O(m) Algorithm for Cores Decomposition of Networks. 2003. [PUMA: core graph network] URL

Stephen B. Seidman. Network structure and minimum degree. Social Networks, (5)3:269 - 287, 1983. [PUMA: core graph network] URL

Ulrik Brandes, Daniel Delling, Marco Gaertler, Robert Görke, Martin Hoefer, Zoran Nikoloski, und Dorothea Wagner. On Finding Graph Clusterings with Maximum Modularity. In Andreas Brandstädt, Dieter Kratsch, und Haiko Müller (Hrsg.), Graph-Theoretic Concepts in Computer Science, (4769):121-132, Springer, Berlin / Heidelberg, 2007. [PUMA: clustering graph modularity theory] URL

Emden R. Gansner, und Stephen C. North. An open graph visualization system and its applications to software engineering. Software Practice & Experience, (30)11:1203--1233, John Wiley & Sons, Inc., New York, NY, USA, September 2000. [PUMA: drawing graph graphics graphviz visualization] URL

M. E. J. Newman. Modularity and community structure in networks. Proceedings of the National Academy of Sciences, (103)23:8577--8582, 2006. [PUMA: clustering community graph modularity network structure]

Emden R. Gansner, Yifan Hu, und Stephen G. Kobourov. GMap: Drawing Graphs as Maps. cs.CG, (arXiv:0907.2585v1)Juli 2009. [PUMA: analysis citation drawing gmap graph graphics graphviz network sna social visualization] URL

Christoph Schmitz, Andreas Hotho, Robert Jäschke, und Gerd Stumme. Content Aggregation on Knowledge Bases using Graph Clustering. In York Sure, und John Domingue (Hrsg.), The Semantic Web: Research and Applications, (4011):530-544, Springer, Heidelberg, 2006. [PUMA: 2006 aggregation clustering content graph itegpub l3s myown nepomuk ontologies ontology seminar2006 theory] URL

Folke Mitzlaff, Dominik Benz, Gerd Stumme, und Andreas Hotho. Visit me, click me, be my friend: An analysis of evidence networks of user relationships in Bibsonomy. Proceedings of the 21st ACM conference on Hypertext and hypermedia, Toronto, Canada, 2010. [PUMA: 2010 analysis evidence_networks graph itegpub myown social_links social_network user_relationships] URL

Yuan An, Jeannette Janssen, und Evangelos E. Milios. Characterizing and Mining the Citation Graph of the Computer Science Literature. Knowl. Inf. Syst., (6):664--678, Springer-Verlag New York, Inc., New York, NY, USA, November 2004. [PUMA: 10th Citation characterizing citation computer graph mining] URL

U. Brandes, und T. Willhalm. Visualization of bibliographic networks with a reshaped landscape metaphor. Proceedings of the symposium on Data Visualisation 2002, 159--ff, Eurographics Association, Aire-la-Ville, Switzerland, Switzerland, 2002. [PUMA: bibliographic bibliography citation graph networks sna] URL

Tsuyoshi Murata. Modularities for Bipartite Networks. HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia, ACM, New York, NY, USA, Juli 2009. [PUMA: ht09 graph bipartite]

Andreas Hotho, Robert Jäschke, Christoph Schmitz, und Gerd Stumme. Information Retrieval in Folksonomies: Search and Ranking. In York Sure, und John Domingue (Hrsg.), The Semantic Web: Research and Applications, (4011):411-426, Springer, Heidelberg, Juni 2006. [PUMA: 2006 folkrank folksonomy graph iccs_example information l3s mining ol_web2.0 pagerank rank ranking retrieval search seminar2006 testttag trias_example webzu widely_related]

Folke Mitzlaff, Dominik Benz, Gerd Stumme, und Andreas Hotho. Visit me, click me, be my friend: An analysis of evidence networks of user relationships in Bibsonomy. Proceedings of the 21st ACM conference on Hypertext and hypermedia, Toronto, Canada, 2010. [PUMA: graph social_links social_network myown evidence_networks 2010 analysis user_relationships itegpub] URL

Jürgen Lerner. Role Assignments. In Ulrik Brandes, und Thomas Erlebach (Hrsg.), Network Analysis, (3418):216-252, Springer, Berlin / Heidelberg, 2005. [PUMA: assignments graph lerner network roles sna social structural] URL

Soumen Chakrabarti, Amit Pathak, und Manish Gupta. Index design and query processing for graph conductance search. The VLDB Journal, 1-26, Springer, Berlin / Heidelberg, 2010. [PUMA: design graph index interactive pagerank processing query toRead folkrank] URL

Lorenzo Isella, Juliette Stehlé, Alain Barrat, Ciro Cattuto, Jean-François Pinton, und Wouter Van den Broeck. What's in a crowd? Analysis of face-to-face behavioral networks. CoRR, (abs/1006.1260)2010. [PUMA: analysis contact crowd graph network rfid social to venus] URL

Rumi Ghosh, und Kristina Lerman. Structure of Heterogeneous Networks. 2009. [PUMA: graph graphs heterogenous measures multi-mode networks sna] URL

MEJ Newman. Finding community structure in networks using the eigenvectors of matrices. Physical Review E, (74)3:36104, APS, 2006. [PUMA: community detection graph modularity spectral theory]

F. R. K. Chung. Spectral Graph Theory. American Mathematical Society, 1997. [PUMA: graph spectral theory]

B. Monien. On Spectral Bounds for the k-Partitioning of Graphs. 2001. [PUMA: graph spectral theory]

Marianna Bolla, und Gábor Tusnády. Spectra and optimal partitions of weighted graphs. Discrete Math., (128)1-3:1--20, Elsevier Science Publishers B. V., Amsterdam, The Netherlands, The Netherlands, 1994. [PUMA: graph spectral the] URL

B. Mohar. The Laplacian spectrum of graphs. Graph Theory, Combinatorics, and Applications, (2):871--898, New York: Wiley, 1991. [PUMA: graph laplacian spectral survey theory]

D.A. Spielman. Spectral Graph Theory and its Applications. Foundations of Computer Science, 2007. FOCS '07. 48th Annual IEEE Symposium on, 29-38, Oktober 2007. [PUMA: graph spectral theory]

David S. Johnson, und Christos H. Papadimitriou. On generating all maximal independent sets. Inf. Process. Lett., (27)3:119--123, Elsevier North-Holland, Inc., Amsterdam, The Netherlands, The Netherlands, 1988. [PUMA: complexity graph independent sets theory] URL

Vânia M.F. Dias, Celina M.H. de Figueiredo, und Jayme L. Szwarcfiter. Generating bicliques of a graph in lexicographic order. Theoretical Computer Science, (337)1-3:240 - 248, 2005. [PUMA: conp graph independent set theory] URL

M. Fiedler. A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory. Czechoslovak Mathematical Journal, (25)100:619--633, 1975. [PUMA: graph spectral theory]

T.H. Haveliwala, und S.D. Kamvar. The second eigenvalue of the Google matrix. A Stanford University Technical Report http://dbpubs. stanford. edu, 2003. [PUMA: graph pagerank spectral theory]

Inderjit S. Dhillon. Co-clustering documents and words using bipartite spectral graph partitioning. KDD '01: Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, 269--274, ACM Press, New York, NY, USA, 2001. [PUMA: community detection graph spectral theory] URL

Guy Blelloch. Graph Separators. 2002. [PUMA: graph separators theory]

A. Pothen, H.D. Simon, und K.P. Liou. Partitioning Sparse Matrices with Eigenvectors of Graphs. SIAM J. MATRIX ANAL. APPLIC., (11)3:430--452, 1990. [PUMA: clustering community graph partitioning spectral theory] URL

Pak K. Chan, Martine D. F. Schlag, und Jason Y. Zien. Spectral K-way ratio-cut partitioning and clustering.. IEEE Trans. on CAD of Integrated Circuits and Systems, (13)9:1088-1096, 1994. [PUMA: community detection graph partitioning spectral theory] URL

Stella X. Yu, und Jianbo Shi. Multiclass Spectral Clustering. Proc. International Conference on Computer Vision (ICCV 03), Nice, France, Oktober 2003. [PUMA: Spectral graph partitioning theory]

Lars W. Hagen, und Andrew B. Kahng. New spectral methods for ratio cut partitioning and clustering.. IEEE Trans. on CAD of Integrated Circuits and Systems, (11)9:1074-1085, 1992. [PUMA: graph partitioning spectral theory] URL

Panagiotis Symeonidis, Alexandros Nanopoulos, und Yannis Manolopoulos. Tag recommendations based on tensor dimensionality reduction. RecSys '08: Proceedings of the 2008 ACM conference on Recommender systems, 43--50, ACM, New York, NY, USA, 2008. [PUMA: community detection graph recommender spectral tag theory] URL

A.G. Ranade. Some uses of spectral methods. 2000. [PUMA: clustering graph spectral svd theory]

S. White, und P. Smyth. A spectral clustering approach to finding communities in graph. SIAM Data Mining, 2005. [PUMA: community detection graph spectral theory]

A. L. Barabasi, und R. Albert. Emergence of scaling in random networks. Science, (286)5439:509--512, Department of Physics, University of Notre Dame, Notre Dame, IN 46556, USA., Oktober 1999. [PUMA: graph network properties statistics] URL

MEJ Newman. Modularity and community structure in networks. Proceedings of the National Academy of Sciences, (103)23:8577--8582, National Acad Sciences, 2006. [PUMA: community detection graph modularity spectral theory]

Charles J. Alpert, Andrew B. Kahng, und So zen Yao. Spectral partitioning: The more eigenvectors, the better. Proc. ACM/IEEE Design Automation Conf, 195--200, 1995. [PUMA: community detection graph spectral theory]

M. E. J. Newman. The structure and function of complex networks. SIAM Review, (45)2:167-256, 2003. [PUMA: graph introduction network review survey theory]

Linton C. Freeman. A Set of Measures of Centrality Based on Betweenness. Sociometry, (40)1:35--41, American Sociological Association, März 1977. [PUMA: betweeness centrality graph sna theory] URL

M. Filippone, F. Camastra, F. Masulli, und S. Rovetta. A survey of kernel and spectral methods for clustering. Pattern recognition, (41)1:176--190, Elsevier, 2008. [PUMA: community detection graph kernel spectral survey theory]

D. Verma, und M. Meila. A comparison of spectral clustering algorithms. University of Washington, Tech. Rep. UW-CSE-03-05-01, 2003. [PUMA: community detection graph spectral theory]

Ulrike Luxburg. A tutorial on spectral clustering. Statistics and Computing, (17)4:395--416, Kluwer Academic Publishers, Hingham, MA, USA, 2007. [PUMA: community detection graph spectral theory] URL

E. Estrada, und J.A. Rodr\'ıguez-Velázquez. Spectral measures of bipartivity in complex networks. SIAM Rev Phys Rev E, (72):046105, APS, 2003. [PUMA: bipartite community detection graph modularity spectral theory]

B. Mohar. Some applications of Laplace eigenvalues of graphs. Graph Symmetry: Algebraic Methods and Applications, (497):227--275, Kluwer, 1997. [PUMA: graph laplacian spectral survey theory]

Daniel A. Spielman, und Shang Teng. Spectral Partitioning Works: Planar Graphs and Finite Element Meshes. University of California at Berkeley, Berkeley, CA, USA, 1996. [PUMA: clustering community detection graph spectral survey theory]

Inderjit S. Dhillon, Yuqiang Guan, und Brian Kulis. A Unified View of Kernel k-means, Spectral Clustering and Graph Cuts. TR-04-252005. [PUMA: community detection graph k-means spectral theory] URL

S.K. Butler. Eigenvalues and Structures of Graphs. 2008. [PUMA: graph spectral theory]

S. Butler. Cospectral graphs for both the adjacency and normalized Laplacian matrices. 2000. [PUMA: bipartite graph spectral theory]

Steve Butler. Spectral Graph Theory: Cheeger constants and discrepancy. 2006. [PUMA: graph introduction spectral theory]

Steve Butler. Spectral Graph Theory: Applications of Courant Fischer. 2006. [PUMA: graph spectral theory]

Steve Butler. Spectral Graph Theory: Three common spectra. 2006. [PUMA: graph introduction spectral theory]

S. Guattery, und G.L. Miller. On the quality of spectral separators. SIAM Journal on Matrix Analysis and Applications, (19)3:701--719, Philadelphia, Pa.: The Society, c1988-, 1998. [PUMA: graph spectral theory]

W.E. Donath, und A.J. Hoffman. Lower bounds for the partitioning of graphs. IBM Journal of Research and Development, (17)5:420--425, 1973. [PUMA: clustering community detection graph spectral theory]

Andrew Y. Ng, Michael I. Jordan, und Yair Weiss. On spectral clustering: Analysis and an algorithm. Advances in Neural Information Processing Systems 14, 849--856, MIT Press, 2001. [PUMA: clustering community detection graph spectral theory]

Béla Bollobás*, und Oliver Riordan. The Diameter of a Scale-Free Random Graph. Combinatorica, (24)1:5--34, Januar 2004. [PUMA: diameter distance geodesic graph mean random] URL

M. Karonski. A review of random graphs. Journal of Graph Theory, (6)4Wiley Subscription Services, Inc., A Wiley Company New York, 1982. [PUMA: graph random theory]

O. Frank. Random sampling and social networks: a survey of various approaches. Math. Sci. Humaines, (104):19--33, 1988. [PUMA: graph random review sna theory]

B. Bollobas. The diameter of random graphs. Transactions of the American Mathematical Society, 41--52, American Mathematical Society, 1981. [PUMA: diameter graph random]

MEJ Newman, SH Strogatz, und DJ Watts. Random graphs with arbitrary degree distributions and their applications. Arxiv preprint cond-mat/0007235, 2001. [PUMA: configuration degree distribution function generating graph model random]

M. Molloy, und B. Reed. A critical point for random graphs with a given degree sequence. Random Structures & Algorithms, (6):161-179, 1995. [PUMA: component configuration giant graph model random theory] URL

B. Soderberg. General formalism for inhomogeneous random graphs. Phys. Rev. E, (66)6:066121, APS, 2002. [PUMA: graph k-partite random theory]

C.J. Anderson, S. Wasserman, und B. Crouch. A p* primer: Logit models for social networks. Social Networks, (21)1:37--66, Elsevier, 1999. [PUMA: carlo exponential generation graph model monte random simulation sna]

T.A.B. Snijders. Markov chain Monte Carlo estimation of exponential random graph models. Journal of Social Structure, (3)2:1--40, 2002. [PUMA: carlo estimation exponential generation graph model monte p* parameter sna]

G. Karypis, R. Aggarwal, V. Kumar, und S. Shekhar. Multilevel hypergraph partitioning: Application in VLSI domain. Proceedings of the 34th annual conference on Design automation, 526--529, 1997. [PUMA: clustering community detection graph hypergraph]

George Karypis, und Vipin Kumar. Multilevel k-way Hypergraph Partitioning. In Proceedings of the Design and Automation Conference, 343--348, 1998. [PUMA: clustering community detection graph hypergraph partitioning]

W. Aiello, F. Chung, und L. Lu. A random graph model for massive graphs. Proceedings of the thirty-second annual ACM symposium on Theory of computing, 171--180, 2000. [PUMA: graph pagerank random simrank surfer] URL

Sergey Brin, und Lawrence Page. The Anatomy of a Large-Scale Hypertextual Web Search Engine. Computer Networks and ISDN Systems, 107--117, 1998. [PUMA: graph pagerank] URL

A.N. Langville, und C.D. Meyer. Deeper inside pagerank. Internet Mathematics, (1)3:335--380, AK Peters, 2004. [PUMA: graph pagerank] URL

U. Brandes, M. Gaertler, und D. Wagner. Experiments on graph clustering algorithms. Lecture notes in computer science, 568--579, Springer, 2003. [PUMA: algorithm clustering community detection evaluation graph] URL

G.W. Flake, R.E. Tarjan, und K. Tsioutsiouliklis. Graph clustering and minimum cut trees. Internet Mathematics, (1)4:385--408, AK Peters, 2004. [PUMA: clustering community detection graph] URL

I. Cantador, und P. Castells. Building Emergent Social Networks and Group Profiles by Semantic User Preference Clustering. 2006. [PUMA: clustering community detection graph]

G. Frivolt, und O. Pok. Comparison of Graph Clustering Approaches. 2006. [PUMA: clustering graph survey]

Francis Maes, Stéphane Peters, Ludovic Denoyer, und Patrick Gallinari. Simulated Iterative Classification A New Learning Procedure for Graph Labeling.. In Wray L. Buntine, Marko Grobelnik, Dunja Mladenic, und John Shawe-Taylor (Hrsg.), ECML/PKDD (2), (5782):47-62, Springer, 2009. [PUMA: 2009 classification ecml graph iterative label labeling multi pkdd] URL

Leman Akoglu, und Christos Faloutsos. RTG: A Recursive Realistic Graph Generator Using Random Typing.. In Wray L. Buntine, Marko Grobelnik, Dunja Mladenic, und John Shawe-Taylor (Hrsg.), ECML/PKDD (1), (5781):13-28, Springer, 2009. [PUMA: 2009 ecml generator graph law pkdd power properties] URL

Matthew Jackson. Average Distance, Diameter, and Clustering in Social Networks with Homophily. Internet and Network Economics, 4--11, 2008. [PUMA: generator graph homophily properties] URL

Michele Berlingerio, Francesco Bonchi, Björn Bringmann, und Aristides Gionis. Mining Graph Evolution Rules.. In Wray L. Buntine, Marko Grobelnik, Dunja Mladenic, und John Shawe-Taylor (Hrsg.), ECML/PKDD (1), (5781):115-130, Springer, 2009. [PUMA: 2009 ecml evolution generation graph pkdd time] URL

Johannes Fürnkranz, Eyke Hüllermeier, und Stijn Vanderlooy. Binary Decomposition Methods for Multipartite Ranking. Machine Learning and Knowledge Discovery in Databases, 359--374, 2009. [PUMA: 2009 ecml graph multipartite pkdd ranking] URL

P. Drineas, A. Frieze, R. Kannan, S. Vempala, und V. Vinay. Clustering large graphs via the singular value decomposition. Machine Learning, (56)1:9--33, Springer, 2004. [PUMA: clustering graph svd vldb] URL

S.E. Schaeffer. Graph clustering. Computer Science Review, (1)1:27--64, Elsevier, 2007. [PUMA: clustering community detection graph] URL

V. Nicosia, G. Mangioni, V. Carchiolo, und M. Malgeri. Extending the definition of modularity to directed graphs with overlapping communities. 2008. [PUMA: COMMUNE community directed graph modularity network overlapping] URL