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» Relevance Feedback Models for Recommendation
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CCIA
2005
Springer
14 years 2 months ago
Modelling the Human Values Scale in Recommender Systems: A first approach
The objective of this paper is two-fold. The first is to develop a methodology capable of extracting the Human Values Scale (HVS) from the user, with reference to his/her objective...
Javier Guzmán, Gustavo González, Jos...
AUSDM
2007
Springer
107views Data Mining» more  AUSDM 2007»
14 years 2 months ago
Preference Networks: Probabilistic Models for Recommendation Systems
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh
CIKM
2008
Springer
13 years 10 months ago
Passage relevance models for genomics search
We present a passage relevance model for integrating syntactic and semantic evidence of biomedical concepts and topics using a probabilistic graphical model. Component models of t...
Jay Urbain, Ophir Frieder, Nazli Goharian
AIRS
2009
Springer
14 years 3 months ago
A Latent Dirichlet Framework for Relevance Modeling
Relevance-based language models operate by estimating the probabilities of observing words in documents relevant (or pseudo relevant) to a topic. However, these models assume that ...
Viet Ha-Thuc, Padmini Srinivasan
SIGIR
2009
ACM
14 years 3 months ago
Approximating true relevance distribution from a mixture model based on irrelevance data
Pseudo relevance feedback (PRF), which has been widely applied in IR, aims to derive a distribution from the top n pseudo relevant documents D. However, these documents are often ...
Peng Zhang, Yuexian Hou, Dawei Song