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Internetalgorithmen WS 2009/10

  Inhalt | Termine | Literatur | Hinweise
  1. M. Crochemore and D. Perrin. Two-Way String-Matching. J. ACM 38(3): 651-675 (1991). (pdf)
  2. D. Breslauer. Saving Comparisons in the Crochemore-Perrin String-Matching Algorithm. Theor. Comput. Sci. 158(1&2): 177-192 (1996) (pdf)
  3. D. Gusfield. Algorithms on Strings, Trees, and Sequences - Computer Science and Computational Biology. Cambridge University Press 1997, Kapitel 5.
  4. G. Navarro. A guided tour to Approximate String Matching. ACM Comput. Surv. 33(1): 31-88 (2001). (pdf)
  5. G. Myers. A Fast Bit-Vector Algorithm for Approximate String Matching Based on Dynamic Programming. J. ACM 46(3): 395-415 (1999) (pdf)
  6. A. Langville and C. Meyer. A survey of eigenvector methods for web information retrieval. SIAM Review, 2005. (pdf)
  7. L. Page, S. Brin, R. Motwani, T. Winograd. The pagerank citation ranking: Bringing order to the web. (doc).
  8. Deeper Inside PageRank. Internet Mathematics 1(3): (2003) (pdf)
  9. J. M. Kleinberg. Authoritative Sources in a Hyperlinked Environment. J. ACM 46(5): 604-632 (1999) (pdf)
  10. R. Lempel, S. Moran. The stochastic approach for link-structure analysis (SALSA) and the TKC effect. Computer Networks 33(1-6): 387-401 (2000) (pdf)
  11. R. Lempel, S. Moran. SALSA: the stochastic approach for link-structure analysis. ACM Trans. Inf. Syst. 19(2): 131-160 (2001) (pdf)
  12. A. Mehta, A. Saberi, U. V. Vazirani, V. V. Vazirani: AdWords and Generalized On-line Matching. FOCS 2005: 264-273 (pdf)
  13. N. Immorlica, K. Jain, M. Mahdian, K. Talwar: Click Fraud Resistant Methods for Learning Click-Through Rates. WINE 2005: 34-45 (pdf)
  14. Giles, Lawrence, Pennock, Rusmevichientong. Methods for Sampling Pages Uniformly from the World Wide Web. AAAI Fall Symposium, 2001. (pdf)
  15. M. Henzinger, A. Heydon, M. Mitzenmacher, M. Najork. On Near Uniform URL Sampling. Computer Networks 33(1-6): 295-308 (2000). (pdf)
  16. G. W. Flake, S. Lawrence, C. L. Giles, F. Coetzee. Self-Organization and Identification of Web Communities. IEEE Computer 35(3): 66-71 (2002) (pdf)
  17. G. W. Flake, R. E. Tarjan, K. Tsioutsiouliklis. Graph Clustering and Minimum Cut Trees. Internet Mathematics 1(4): (2003) (pdf)
  18. J. Leskovec, K. Lang, A. Dasgupta, M. Mahoney. Statistical Properties of Community Structure in Large Social and Information Networks World Wide Web (WWW), 2008. (pdf)
  19. E. K. Lua, J. Crowcroft, M. Pias, R. Sharma, S. Lim. A survey and comparison of peer-to-peer overlay network schemes. IEEE Communications Surveys and Tutorials 7(1-4): 72-93 (2005) (pdf)
  20. I. Stoica, R. Morris, D. Liben-Nowell, D. R. Karger, M. F. Kaashoek, F. Dabek, H. Balakrishnan. Chord: a scalable peer-to-peer lookup protocol for internet applications. IEEE/ACM Trans. Netw. 11(1): 17-32 (2003) (pdf)
  21. R. Guerraoui, S. B. Handurukande, K. Huguenin, A.M. Kermarrec, F. Le Fessant, E. Riviere. GosSkip, an Efficient, Fault-Tolerant and Self Organizing Overlay Using Gossip-based Construction and Skip-Lists Principles. Peer-to-Peer Computing 2006: 12-22 (pdf)