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SIGIR
2009
ACM
14 years 2 months ago
Learning to rank for quantity consensus queries
Web search is increasingly exploiting named entities like persons, places, businesses, addresses and dates. Entity ranking is also of current interest at INEX and TREC. Numerical ...
Somnath Banerjee, Soumen Chakrabarti, Ganesh Ramak...
KDD
2005
ACM
143views Data Mining» more  KDD 2005»
14 years 8 months ago
SVM selective sampling for ranking with application to data retrieval
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Hwanjo Yu
CIKM
2009
Springer
14 years 2 months ago
A general markov framework for page importance computation
We propose a General Markov Framework for computing page importance. Under the framework, a Markov Skeleton Process is used to model the random walk conducted by the web surfer on...
Bin Gao, Tie-Yan Liu, Zhiming Ma, Taifeng Wang, Ha...
IUI
2003
ACM
14 years 26 days ago
Adapting to the user's internet search strategy on small devices
World Wide Web search engines typically return thousands of results to the users. To avoid users browsing through the whole list of results, search engines use ranking algorithms ...
Jean-David Ruvini
WSDM
2009
ACM
114views Data Mining» more  WSDM 2009»
14 years 2 months ago
Wikipedia pages as entry points for book search
A lot of the world’s knowledge is stored in books, which, as a result of recent mass-digitisation efforts, are increasingly available online. Search engines, such as Google Book...
Marijn Koolen, Gabriella Kazai, Nick Craswell