A genetic algorithm for dynamic modelling and prediction of activity in document streams

Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference

Volumn , Issue , 2007, Pages 1896-1903

  Araujo, Lourdes ^a   Merelo, Juan Julian ^b  

^a UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

^b UNIVERSITY OF GRANADA   (Spain)

Author keywords

Buzz detection; Event stream modelling; Evolutionary algorithms; Online text streams

Indexed keywords

DATA ACQUISITION; DYNAMIC MODELS; SEARCH ENGINES;

BUZZ DETECTION; EVENT STREAM MODELING; ONLINE TEXT STREAMS;

GENETIC ALGORITHMS;

EID: 34548085705     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1276958.1277340     Document Type: Conference Paper

References (11)

1. J. Allan. Topic Detection and Tracking: Event-Based Information Organization. Kluwer Academic Publishers, 2002.
2. J. Allan, J. Carbonell, G. Doddington, J. Yamron, and Y. Yang. Topic detection and tracking pilot study, 1998.
3. E. Bingham, A. Kabán, and M. Girolami. Topic identification in dynamical text by complexity pursuit. Neural Process. Lett., 17(1):69-83, 2003.
4. M. Charikar, K. Chen, and M. Farach-Colton. Finding frequent items in data streams. In M. Charikar, K. Chen, and M. Farach-Colton. Finding frequent items in data streams. In Proceedings of the 29th International Colloquium on Automata, Languages, and Programming, 2002., 2002.
5. A. I. Elwalid and D. Mitra. Effective bandwidth of general markovian traffic sources and admission control of high speed networks. IEEE/ACM Trans. Netw., 1(3):329-343, 1993.
6. G. D. Forney. The Viterbi algorithm. Proceedings of The IEEE, 61(3):268-278, 1973.
7. M. Girolami and A. Kaban. Simplicial mixtures of Markov chains: Distributed modelling of dynamic user profiles. In S. Thrun, L. Saul, and B. Schölkopf, editors, Advances in Neural Information Processing Systems 16. MIT Press, Cambridge, MA, 2004.
8. J. Kleinberg. Bursty and hierarchical structure in streams. In Proc. 8th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, pages 91-101. ACM, 2002.
9. J. Kleinberg. Temporal dynamics of on-line information streams. In M. Garofalakis, J. Gehrke, and R. Rastogi, editors, Data Stream Management: Processing High-Speed Data Streams (to appear). Springer, 2005.
10. R. Papka. On-line New Event Detection, Clustering and Tracking. PhD thesis, Department of Computer Science, University of Massachusetts, 1999.
11. L. R. Rabiner. A tutorial on hidden Markov models and selected applications in speech recognition. In Readings in speech recognition, pages 267-296. Morgan Kaufmann Publishers Inc., 1990.