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» Ranking Query Results using Context-Aware Preferences
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IPM
2008
100views more  IPM 2008»
15 years 4 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
146
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JUCS
2008
117views more  JUCS 2008»
15 years 4 months ago
Ranking Retrieval Systems with Partial Relevance Judgements
: Some measures such as mean average precision and recall level precision are considered as good system-oriented measures, because they concern both precision and recall that are t...
Shengli Wu, Fabio Crestani
WWW
2008
ACM
16 years 5 months ago
Learning to rank relational objects and its application to web search
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
SIGIR
2004
ACM
15 years 9 months ago
Learning effective ranking functions for newsgroup search
Web communities are web virtual broadcasting spaces where people can freely discuss anything. While such communities function as discussion boards, they have even greater value as...
Wensi Xi, Jesper Lind, Eric Brill
ECIR
2007
Springer
15 years 5 months ago
Feature- and Query-Based Table of Contents Generation for XML Documents
The availability of a document’s logical structure in XML retrieval allows retrieval systems to return document portions (elements) instead of whole documents. This helps searche...
Zoltán Szlávik, Anastasios Tombros, ...