Characterization of graphs using degree cores

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4936 LNCS, Issue , 2008, Pages 137-148

  Healy, John ^a   Janssen, Jeannette ^a   Milios, Evangelos ^a   Aiello, William ^b  

^a DALHOUSIE UNIVERSITY   (Canada)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION; IMAGE RETRIEVAL; TREES (MATHEMATICS);

CO-AUTHORSHIP; GENERATIVE MODELING; HIERARCHICAL TREES; LOCAL STRUCTURES; MINIMAL DEGREE; OF GRAPHS; REAL-WORLD GRAPHS; SUB GRAPHS; WEB GRAPHS;

GRAPH THEORY;

EID: 49149091267     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-78808-9_13     Document Type: Conference Paper

References (23)

1. Pržulj, N., Corneil, D.G., Jurisica, I.: Modeling interactome: scale-free or geometric? Bioinformatics 20(18), 3508-3515
2. Batagelj, V.: Zaveršnik, M.: Generalized Cores. ArXiv Computer Science e-prints (2002)
3. Seidman, S.B.: Network structure and minimum degree. Social Networks, 269-287 (1983)
4. Wasserman, S., Faust, K.: Social network analysis: Methods and applications. Cambridge University Press, Cambridge (1994)
5. Alvarez-Hamelin, I., Dall'Asta, L., Barrat, A., Vespignani, A.: DELIS-TR-0166 - k-core decomposition: A tool for the visualization of large scale networks. techreport 0166, DELIS - Dynamically Evolving Large-scale Information Systems (2004)
6. Alvarez-Hamelin, I., Barrat, A., Dall'Asta, L., Vespignani, A.: k-core decomposition: A tool for the analysis of large scale internet graphs. Computer Science, cs.NI/0511007 (2005)
7. Batagelj, V., Mrvar, A.: Pajek - Analysis and Visualization of Large Networks, vol. 2265 (January 2002)
8. Wuchty, S., Almaas, E.: Peeling the yeast protein network. Proteomics (2005)
9. Bader, G.D., Hogue, C.W.: An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics 4, 2 (2003)
10. Gaertler, M., Patrignani, M.: DELIS-TR-0003 - dynamic analysis of the autonomous system graph. In: Proceedings 0003, 2004, IPS 2004 (Inter-Domain Performance and Simulation) (2004)
11. Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer, Heidelberg (2001)
12. Bonato, A.: A survey of models of the web graph. In: Proceedings of the Workshop on Combinatorial and Algorithmic Aspects of Networking (CANN 2004), Springer, Heidelberg (2004)
13. Chung, F., Lu, L., Dewey, T.G., Galas, D.J.: Duplication models for biological networks. Journal of Computational Biology 10(5), 677-687 (2003)
14. TREC: The.gov test collection (last accessed August 28, 2006)
15. Hall, B.H., Jaffe, A.B., Trajtenberg, M.: The nber patent citation data file: Lessons, insights and methodological tools. NBER Working Papers 8498, National Bureau of Economic Research, Inc (October 2001) (last accessed August, 30 2006), http://ideas.repec.org/p/nbr/nberwo/8498.html
16. Wan, X., Janssen, J., Kalyaniwalla, N., Milios, E.: Statistical analysis of dynamic graphs. In: Proceedings of AISB 2006: Adaptation in Artificial and Biological Systems, vol. 3, pp. 176-179 (2006)
17. Angelova, R., Weikum, G.: Graph-based text classification: Learn from your neighbors. In: 29th Annual International ACM SIGIR Conference on Research & Development on Information Retrieval (SIGIR 2006), Association for Computing Machinery (ACM), pp. 485-492. ACM, New York (2006)
18. Erdocombining double acute accents, P., Rényi, A.: On random graphs. Publicationes Mathematicae (1959)
19. Erdocombining double acute accents, P., Rényi, A.: On the evolution of random graphs. Publ. Math. Inst. Hungar. Acad. Sci (1961)
20. Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286, 509-512 (1999)
21. Bollobás, B., Riordan, O., Spencer, J., Tusnády, G.: The degree sequence of a scale-free random graph process. Random Structures Algorithms (2001)
22. Chung, F., Lu, L.: Coupling online and offline analyses for random power law graphs. In: Internet Mathematics (2003)
23. Siek, J.G., Lee, L.Q., Lumsdaine, A.: The boost graph library: User guide and reference manual. Addison-Wesley Longman Publishing Co., Inc., Boston (2002)