A random text model for the generation of statistical language invariants

NAACL HLT 2007 - Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics, Proceedings of the Main Conference

Volumn , Issue , 2007, Pages 105-112

  Biemann, Chris ^a  

^a UNIVERSITY OF LEIPZIG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CO-OCCURRENCE; CO-OCCURRENCE GRAPH; GENERATION PROCESS; NATURAL LANGUAGES; PLAUSIBLE MODEL; RANDOM GENERATION; SENTENCE LENGTH; SMALL WORLDS; TEXT GENERATIONS; TEXT MODELS; WORD FREQUENCIES; WORD LENGTH;

DATA MINING; SEMANTICS;

COMPUTATIONAL LINGUISTICS;

EID: 84858379881     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. C. Allauzen, M. Mohri, and B. Roark. 2003. Generalized algorithms for constructing language models. In Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics, pp. 40-47
2. A.-L. Barabási and R. Albert. 1999. Emergence of scaling in random networks. Science, 286:509-512
3. T. Dunning. 1993. Accurate Methods for the Statistics of Surprise and Coincidence. Computational Linguistics, 19(1), pp. 61-74
4. P. Erdös and A. Rényi. 1959. On Random Graphs I. Publicationes Mathematicae (Debrecen)
5. R. Ferrer i Cancho and R. V. Solé. 2001. The small-world of human language. Proceedings of the Royal Society of London B 268 pp. 2261-2266
6. R. Ferreri Cancho and R. V. Solé. 2002. Zipf's law and random texts. Advances in Complex Systems, Vol.5 No. 1 pp. 1-6
7. L. Q. Ha, E. Sicilia-Garcia, J. Ming and F.J. Smith. 2002. Extension of Zipf's law to words and phrases. Proceedings of 19th International Conference on Computational Linguistics (COLING-2002), pp. 315-320.
8. G. Jäger. 2003. Evolutionary Game Theory and Linguistic Typology: A Case Study. Proceedings of the 14th Amsterdam Colloquium, ILLC, University of Amsterdam, 2003.
9. I. Kanter and D. A. Kessler. 1995. Markov Processes: Linguistics and Zipf's law. Physical review letters, 74:22
10. S. R. Kumar, P. Raghavan, S. Rajagopalan and A. Tomkins. 1999. Extracting Large-Scale Knowledge Bases from the Web. The VLDB Journal, pp. 639-650
11. B. B. Mandelbrot. 1953. An information theory of the statistical structure of language. In Proceedings of the Symposium on Applications of Communications Theory, London
12. M. Matsumoto and T. Nishimura. 1998. Mersenne Twister: A 623-dimensionally equidistributed uniform pseudorandom number generator. ACM Trans. on Modeling and Computer Simulation, Vol. 8, No. 1, pp.3-30
13. G. A. Miller. 1957. Some effects of intermittent silence. American Journal of Psychology, 70, pp. 311-314
14. H. A. Simon. 1955. On a class of skew distribution functions. Biometrika, 42, pp. 425-440
15. B. Sigurd, M. Eeg-Olofsson and J. van de Weijer. 2004. word length, sentence length and frequency - Zipf revisited. Studia Linguistica, 58(1), pp. 37-52 (Pubitemid 40195039)
16. M. Steyvers and J. B. Tenenbaum. 2005. The large-scale structure of semantic networks: statistical analyses and a model of semantic growth. Cognitive Science, 29(1)
17. S. P. Thompson and E. L. Newport. 2007. Statistical learning of syntax: The role of transitional probability. Language Learning and Development, 3, pp. 1-42.
18. D. J. Watts and S. H. Strogatz. 1998. Collective dynamics of small-world networks. Nature, 393 pp. 440-442
19. D. H. Zanette and M. A. Montemurro. 2002. Dynamics of text generation with realistic Zipf distribution. arXiv:cond-mat/0212496
20. G. K. Zipf. 1949. Human Behavior and the Principle of least Effort. Cambridge, MA: Addison Wesley