Jenny Edwards
- 1.B. Brewington and G. Cybenko. How dynamic is the web? In Proceedings of the 9th World Wide Web Conference (WWW9), 2000. Google Scholar
Digital Library
- 2.B. Brewington and G. Cybenko. Keeping up with the changing web. Computer, pages 52{58, May 2000. Google ScholarDigital Library
- 3.S. Brin and L. Page. The anatomy of a large-scale hypertextual web search engine. In Proceedings of the 7th World Wide Web Conference (WWW7), 1998. Google ScholarDigital Library
- 4.A. Broder, S. Glassman, M. Manasse, and G. Zweig. Syntactic clustering of the web. In Proceedings of 6th International World Wide Web Conference (WWW6), 1997. Google ScholarDigital Library
- 5.J. Cho and H. Garcia-Molina. The evolution of the web and implications for an incremental crawler. In Proceedings of 26th International Conference onVery Large Databases (VLDB), 2000. Google ScholarDigital Library
- 6.J. Cho and H. Garcia-Molina. Synchronizing a database to improve freshness. In Proceedings of 2000 ACM International Conference on Management of Data (SIGMOD), 2000. Google ScholarDigital Library
- 7.J. Cho, H. Garcia-Molina, and L. Page. Efficient crawling through URL ordering. In Proceedings of the 7th World Wide Web Conference (WWW7), 1998. Google ScholarDigital Library
- 8.E. Coffman, Z. Liu, and R. Weber. Optimal robot scheduling for web search engines, Rapport de recherche no 3317. Technical report, INRIA Sophia Antipolis, 1997.Google Scholar
- 9.F. Douglis, A. Feldmann, and B. Krishnamurthy. Rate of change and other metrics: a live study of the world wide web. In Proceedings of USENIX Symposium on Internetworking Technologies and Systems, 1997. Google ScholarDigital Library
- 10.A. Heydon and M. Najork. Mercator: A scalable, extensible web crawler. World Wide Web, 2(4):219{229, 1999. Google ScholarDigital Library
- 11.MINOS. (http://www.sbsi-sol-optimize.com/minos.htm).Google Scholar
- 12.NEOS Server for Optimization. (http://www-neos.mcs.anl.gov).Google Scholar
- 13.C. Wills and M. Mikhailov. Towards a better understanding of web resources and server responses for improved caching. In Proceedings of the 8th World Wide Web Conference (WWW8), 1999. Google ScholarDigital Library
Index Terms
- An adaptive model for optimizing performance of an incremental web crawler
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