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» Improving Case-Based Recommendations Using Implicit Feedback
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ECIR
2011
Springer
12 years 11 months ago
Balancing Exploration and Exploitation in Learning to Rank Online
Abstract. As retrieval systems become more complex, learning to rank approaches are being developed to automatically tune their parameters. Using online learning to rank approaches...
Katja Hofmann, Shimon Whiteson, Maarten de Rijke
EWCBR
2004
Springer
14 years 26 days ago
Dynamic Critiquing
Abstract. Critiquing is a powerful style of feedback for case-based recommender systems. Instead of providing detailed feature values, users indicate a directional preference for a...
James Reilly, Kevin McCarthy, Lorraine McGinty, Ba...
CORR
2006
Springer
117views Education» more  CORR 2006»
13 years 7 months ago
Distributed Transmit Beamforming using Feedback Control
The concept of distributed transmit beamforming is implicit in many key results of network information theory. However, its implementation in a wireless network involves the funda...
Raghuraman Mudumbai, J. Hespanha, Upamanyu Madhow,...
IEEEPACT
2009
IEEE
14 years 2 months ago
Using Aggressor Thread Information to Improve Shared Cache Management for CMPs
—Shared cache allocation policies play an important role in determining CMP performance. The simplest policy, LRU, allocates cache implicitly as a consequence of its replacement ...
Wanli Liu, Donald Yeung
IIR
2010
13 years 9 months ago
Context-Dependent Recommendations with Items Splitting
Recommender systems are intelligent applications that help on-line users to tackle information overload by providing recommendations of relevant items. Collaborative Filtering (CF...
Linas Baltrunas, Francesco Ricci