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» Relevance Feedback Models for Recommendation
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CMSB
2006
Springer
14 years 12 days ago
Randomization and Feedback Properties of Directed Graphs Inspired by Gene Networks
Having in mind the large-scale analysis of gene regulatory networks, we review a graph decimation algorithm, called "leaf-removal", which can be used to evaluate the feed...
M. Cosentino Lagomarsino, P. Jona, B. Bassetti
CIKM
2007
Springer
14 years 2 months ago
Query expansion using probabilistic local feedback with application to multimedia retrieval
As one of the most effective query expansion approaches, local feedback is able to automatically discover new query terms and improve retrieval accuracy for different retrieval ...
Rong Yan, Alexander G. Hauptmann
SIGIR
2009
ACM
14 years 3 months ago
Query dependent pseudo-relevance feedback based on wikipedia
Pseudo-relevance feedback (PRF) via query-expansion has been proven to be effective in many information retrieval (IR) tasks. In most existing work, the top-ranked documents from...
Yang Xu, Gareth J. F. Jones, Bin Wang
DEXA
2009
Springer
175views Database» more  DEXA 2009»
14 years 3 months ago
RoK: Roll-Up with the K-Means Clustering Method for Recommending OLAP Queries
Dimension hierarchies represent a substantial part of the data warehouse model. Indeed they allow decision makers to examine data at different levels of detail with On-Line Analyt...
Fadila Bentayeb, Cécile Favre
IUI
2000
ACM
14 years 1 months ago
Learning to recommend from positive evidence
In recent years, many systems and approaches for recommending information, products or other objects have been developed. In these systems, often machine learning methods that nee...
Ingo Schwab, Wolfgang Pohl, Ivan Koychev