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» Learning to rank for information retrieval
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EDBT
2006
ACM
169views Database» more  EDBT 2006»
15 years 10 months ago
Feedback-Driven Structural Query Expansion for Ranked Retrieval of XML Data
Relevance Feedback is an important way to enhance retrieval quality by integrating relevance information provided by a user. In XML retrieval, feedback engines usually generate an ...
Ralf Schenkel, Martin Theobald
ECIR
2010
Springer
14 years 7 months ago
Query Aspect Based Term Weighting Regularization in Information Retrieval
Abstract. Traditional retrieval models assume that query terms are independent and rank documents primarily based on various term weighting strategies including TF-IDF and document...
Wei Zheng, Hui Fang
BMCBI
2010
91views more  BMCBI 2010»
14 years 10 months ago
Ranked retrieval of Computational Biology models
Background: The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. ...
Ron Henkel, Lukas Endler, Andre Peters, Nicolas Le...
ICTIR
2009
Springer
14 years 7 months ago
An Analysis of NP-Completeness in Novelty and Diversity Ranking
Abstract. A useful ability for search engines is to be able to rank objects with novelty and diversity: the top k documents retrieved should cover possible interpretations of a que...
Ben Carterette