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» Maximum Margin Ranking Algorithms for Information Retrieval
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ECIR
2008
Springer
13 years 9 months ago
Utilizing Passage-Based Language Models for Document Retrieval
Abstract. We show that several previously proposed passage-based document ranking principles, along with some new ones, can be derived from the same probabilistic model. We use lan...
Michael Bendersky, Oren Kurland
SIGIR
2004
ACM
14 years 1 months ago
A joint framework for collaborative and content filtering
This paper proposes a novel, unified, and systematic approach to combine collaborative and content-based filtering for ranking and user preference prediction. The framework inco...
Justin Basilico, Thomas Hofmann
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
14 years 8 months ago
Structured learning for non-smooth ranking losses
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...
CIKM
2008
Springer
13 years 9 months ago
Trada: tree based ranking function adaptation
Machine Learned Ranking approaches have shown successes in web search engines. With the increasing demands on developing effective ranking functions for different search domains, ...
Keke Chen, Rongqing Lu, C. K. Wong, Gordon Sun, La...
WSDM
2010
ACM
210views Data Mining» more  WSDM 2010»
14 years 5 months ago
Leveraging Temporal Dynamics of Document Content in Relevance Ranking
Many web documents are dynamic, with content changing in varying amounts at varying frequencies. However, current document search algorithms have a static view of the document con...
Jonathan L. Elsas, Susan T. Dumais