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» Relevance Feedback Models for Recommendation
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CIKM
2009
Springer
13 years 12 months ago
Adaptive relevance feedback in information retrieval
Relevance Feedback has proven very effective for improving retrieval accuracy. A difficult yet important problem in all relevance feedback methods is how to optimally balance the...
Yuanhua Lv, ChengXiang Zhai
MHCI
2009
Springer
13 years 12 months ago
Improving the recommendation of mobile services by interpreting the user's icon arrangement
The aether soon will be pervaded with a high density of digital services for usage on mobile phones. Personalization plays a crucial role for the success and acceptance of such sy...
Matthias Böhmer, Gernot Bauer
CSCW
2006
ACM
13 years 11 months ago
Don't look stupid: avoiding pitfalls when recommending research papers
If recommenders are to help people be more productive, they need to support a wide variety of real-world information seeking tasks, such as those found when seeking research paper...
Sean M. McNee, Nishikant Kapoor, Joseph A. Konstan
ICIP
2002
IEEE
13 years 10 months ago
A graphic-theoretic model for incremental relevance feedback in image retrieval
Many traditional relevance feedback approaches for CBIR can only achieve limited short-term performance improvement without benefiting long-term performance. To remedy this limita...
Yueting Zhuang, Jun Yang 0003, Qing Li, Yunhe Pan
SIGIR
2010
ACM
13 years 9 months ago
Positional relevance model for pseudo-relevance feedback
Pseudo-relevance feedback is an effective technique for improving retrieval results. Traditional feedback algorithms use a whole feedback document as a unit to extract words for ...
Yuanhua Lv, ChengXiang Zhai