Text clustering for peer-to-peer networks with probabilistic guarantees

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

Volumn 5993 LNCS, Issue , 2010, Pages 293-305

  Papapetrou, Odysseas ^a   Siberski, Wolf ^a   Fuhr, Norbert ^b  

^a L3S RESEARCH CENTER   (Germany)

^b UNIVERSITY OF DUISBURG ESSEN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER ANALYSIS; INFORMATION RETRIEVAL; PEER TO PEER NETWORKS; SCALABILITY;

CLUSTERING QUALITY; CURRENT CLUSTERING ALGORITHMS; DISTRIBUTED ENVIRONMENTS; EXPERIMENTAL EVALUATION; HIGH SCALABILITIES; PROBABILISTIC APPROACHES; PROBABILISTIC GUARANTEES; TEXT CLUSTERING;

CLUSTERING ALGORITHMS;

EID: 77952311353     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-12275-0_27     Document Type: Conference Paper

References (18)

1. Blake, C.: A comparison of document, sentence, and term event spaces. In: ACL (2006)
2. Cudŕe-Mauroux, P., Agarwal, S., Aberer, K.: Gridvine: An infrastructure for peer information management. IEEE Internet Computing 11(5) (2007)
3. Datta, S., Giannella, C.R., Kargupta, H.: Approximate distributed K-Means clustering over a peer-to-peer network. IEEE TKDE 21(10), 1372-1388 (2009)
4. Dhillon, I.S., Modha, D.S.: A data-clustering algorithm on distributed memory multiprocessors. In: Workshop on Large-Scale Parallel KDD Systems (1999)
5. Eisenhardt, M., Müller, W., Henrich, A.: Classifying documents by distributed P2P clustering. In: INFORMATIK (2003)
6. Forman, G., Zhang, B.: Distributed data clustering can be efficient and exact. SIGKDD Explor. Newsl. 2(2), 34-38 (2000)
7. Hammouda, K., Kamel, M.: HP2PC: Scalable hierarchically-distributed peer to peer clustering. In: SDM (2007)
8. Haslhofer, B., Knezevíe, P.: The BRICKS digital library infrastructure. In: Semantic Digital Libraries, pp. 151-161 (2009)
9. Hsiao, H.-C., King, C.-T.: Similarity discovery in structured P2P overlays. In: ICPP (2003)
10. Lewis, D.D., Yang, Y., Rose, T.G., Li, F.: RCV1: a new benchmark collection for text categorization research. J. Mach. Learn. Res. 5, 361-397 (2004)
11. Lu, J., Callan, J.: Content-based retrieval in hybrid peer-to-peer networks. In: CIKM 2003, pp. 199-206. ACM, New York (2003)
12. Motwani, R., Raghavan, P.: Randomized Algorithms. Cambridge University Press, Cambridge (1995)
13. Papadimitriou, C.H., Tamaki, H., Raghavan, P., Vempala, S.: Latent semantic indexing: a probabilistic analysis. In: PODS (1998)
14. Papapetrou, O., Siberski, W., Fuhr, N.: Text clustering for P2P networks with probabilistic guarantees. Extended version (2009), http://www.l3s.de/ ~papapetrou/publications/pcp2p-ecir-ext.pdf
15. Steyvers, M., Griffiths, T.: Handbook of Latent Semantic Analysis. In: Probabilistic Topic Models, pp. 427-448. Lawrence Erlbaum, Mahwah (2007)
16. Stoica, I., Morris, R., Karger, D., Kaashoek, F., Balakrishnan, H.: Chord: A scalable peer-to-peer lookup service for internet applications. In: SIGCOMM (2001)
17. Xu, J., Croft, W.B.: Cluster-based language models for distributed retrieval. In: SIGIR (1999)
18. Zipf, G.K.: Human Behavior and the Principle of Least-Effort. Addison-Wesley, Cambridge (1949)