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» Learning to rank for information retrieval
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WWW
2008
ACM
15 years 10 months ago
Mining the search trails of surfing crowds: identifying relevant websites from user activity
The paper proposes identifying relevant information sources from the history of combined searching and browsing behavior of many Web users. While it has been previously shown that...
Mikhail Bilenko, Ryen W. White
68
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CIKM
2008
Springer
14 years 11 months ago
Error-driven generalist+experts (edge): a multi-stage ensemble framework for text categorization
We introduce a multi-stage ensemble framework, ErrorDriven Generalist+Expert or Edge, for improved classification on large-scale text categorization problems. Edge first trains a ...
Jian Huang 0002, Omid Madani, C. Lee Giles
NAACL
1994
14 years 11 months ago
Learning from Relevant Documents in Large Scale Routing Retrieval
The normal practice of selecting relevant documents for training routing queries is to either use all relevants or the 'best n' of them after a (retrieval) ranking opera...
K. L. Kwok, Laszlo Grunfeld
IPM
2008
133views more  IPM 2008»
14 years 9 months ago
DistanceRank: An intelligent ranking algorithm for web pages
A fast and efficient page ranking mechanism for web crawling and retrieval remains as a challenging issue. Recently, several link based ranking algorithms like PageRank, HITS and ...
Ali Mohammad Zareh Bidoki, Nasser Yazdani
ICDIM
2007
IEEE
15 years 4 months ago
Several methods of ranking retrieval systems with partial relevance judgment
: Some measures such as average precision over all relevant documents and recall level precision are considered as good system-oriented measures, because they concern both precisio...
Shengli Wu, Sally I. McClean