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WSDM
2010
ACM
242views Data Mining» more  WSDM 2010»
14 years 7 months ago
Improving Ad Relevance in Sponsored Search
We describe a machine learning approach for predicting sponsored search ad relevance. Our baseline model incorporates basic features of text overlap and we then extend the model t...
Dustin Hillard, Stefan Schroedl, Eren Manavoglu, H...
ICDE
2009
IEEE
170views Database» more  ICDE 2009»
14 years 11 months ago
Semantics of Ranking Queries for Probabilistic Data and Expected Ranks
Abstract-- When dealing with massive quantities of data, topk queries are a powerful technique for returning only the k most relevant tuples for inspection, based on a scoring func...
Graham Cormode, Feifei Li, Ke Yi
CIVR
2006
Springer
201views Image Analysis» more  CIVR 2006»
14 years 1 months ago
Efficient Margin-Based Rank Learning Algorithms for Information Retrieval
Learning a good ranking function plays a key role for many applications including the task of (multimedia) information retrieval. While there are a few rank learning methods availa...
Rong Yan, Alexander G. Hauptmann
SIGIR
2006
ACM
14 years 3 months ago
Improving web search ranking by incorporating user behavior information
We show that incorporating user behavior data can significantly improve ordering of top results in real web search setting. We examine alternatives for incorporating feedback into...
Eugene Agichtein, Eric Brill, Susan T. Dumais
ACMSE
2004
ACM
14 years 3 months ago
SA_MetaMatch: relevant document discovery through document metadata and indexing
SA_MetaMatch, a component of the Standards Advisor (SA), is designed to find relevant documents through matching indices of metadata and document content. The elements in the meta...
Hiu S. Yau, J. Scott Hawker