Selection in scale-free small world

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

Volumn 3690 LNAI, Issue , 2005, Pages 579-582

  Palotai, Zsolt ^a   Farkas, Csilla ^b   Lorincz, András ^b  

^a EÖTVÖS LORÁND UNIVERSITY   (Hungary)

^b UNIVERSITY OF SOUTH CAROLINA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; DATA REDUCTION; INFORMATION ANALYSIS; LEARNING ALGORITHMS; WORLD WIDE WEB;

REINFORCEMENT LEARNING; SCALE-FREE SMALL WORLD (SFSW) STRUCTURE; WEB CRAWLERS;

LARGE SCALE SYSTEMS;

EID: 33646141866     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11559221_65     Document Type: Conference Paper

References (6)

1. Barabási, A., Albert, R., Jeong, H.: Scale-free characteristics of random networks: The topology of the world wide web. Physica A 281 (2000) 69-77
2. Kleinberg, J., Lawrence, S.: The structure of the web. Science 294 (2001) 1849-1850
3. Kókai, I., Lo″rincz, A.: Fast adapting value estimation based hybrid architecture for searching the world-wide web. Applied Soft Computing 2 (2002) 11-23
4. Lo″rincz, A., Kókai, I., Meretei, A.: Intelligent high-performance crawlers used to reveal topic-specific structure of the WWW. Int. J. Founds. Comp. Sci. 13 (2002) 477-495
5. Rennie, J., Nigam, K., McCallum, A.: Using reinforcement learning to spider the web efficiently. In: Proc. 16th Int. Conf. on Machine Learning (ICML), Morgan Kaufmann, San Francisco (1999) 335-343
6. Palotai, Z., Farkas, C., Lo″rincz, A.: Selection in scale free small world. http://www.arxiv.org/pdf/cs.LG/0504063 (2005)