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Abstract: Consider the task of exploring the Web in order to find pages of a particular kind or on a particular topic. This task arises in the construction of domain-specific search engines. A selective, directed web spider can be much more efficient than a spider that gathers new pages indiscriminantly. This paper argues that the creation of efficient web spiders is best framed and solved by reinforcement learning, a branch of machine learning that concerns itself with optimal sequential decision... (Update)
Context of citations to this paper: More
.... first search [12] pagerank [4,8,15] focused crawling [17,10] shark search [11] adaptive agent [2,3,9] reinforcement learning [6], artificial life agent[13] arbitrary predicate [1] WTMS [18,19] etc. The main purpose of these algorithms is to gather the most relevant...
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BibTeX entry: (Update)
J. Rennie and A. McCallum. "Efficient Web Spidering with Reinforcement Learning." In Proceedings of the 16th International Conference on Machine Learning, 1999. http://citeseer.ist.psu.edu/rennie99efficient.html More
@misc{ rennie-efficient,
author = "Jason Rennie and Andrew {McCallum}",
title = "Efficient Web Spidering with Reinforcement Learning",
url = "citeseer.ist.psu.edu/rennie99efficient.html" }
Citations (may not include all citations):976 Machine Learning (context) - Mitchell - 1997
374 Reinforcement learning: A survey - Kaelbling, Littman et al. - 1996
189 Webwatcher: A tour guide for the World Wide Web - Joachims, Freitag et al. - 1997
103 at forty: The independence assumption in information retriev.. (context) - Lewis - 1998
29 Text classication from labeled and unlabeled documents using.. - Nigam, McCallum et al. - 1999
7 Building domain-specic search engines with machine learning .. - McCallum, Nigam et al. - 1999
4 Elements of Information Theory (context) - Networks, Systems et al. - 1991
2 ARACHNID: Adaptive retrieval agents choosing heuristic neigh.. (context) - AAAI-, on et al. - 1997
2 and Shoham (context) - Balabanovic - 1995
1 Regression using classication algorithms (context) - Learning, Torgo et al. - 1997
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