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» On Modelling User Observations in the UTP
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KDD
2012
ACM
212views Data Mining» more  KDD 2012»
11 years 10 months ago
eTrust: understanding trust evolution in an online world
Most existing research about online trust assumes static trust relations between users. As we are informed by social sciences, trust evolves as humans interact. Little work exists...
Jiliang Tang, Huan Liu, Huiji Gao, Atish Das Sarma...
IDA
2009
Springer
14 years 2 months ago
Two-Way Grouping by One-Way Topic Models
Abstract. We tackle the problem of new users or documents in collaborative filtering. Generalization over users by grouping them into user groups is beneficial when a rating is t...
Eerika Savia, Kai Puolamäki, Samuel Kaski
CSL
2012
Springer
12 years 3 months ago
Reinforcement learning for parameter estimation in statistical spoken dialogue systems
Reinforcement techniques have been successfully used to maximise the expected cumulative reward of statistical dialogue systems. Typically, reinforcement learning is used to estim...
Filip Jurcícek, Blaise Thomson, Steve Young
OHS
2001
Springer
13 years 12 months ago
Link Augmentation: A Context-Based Approach to Support Adaptive Hypermedia
In today’s adaptive hypermedia systems, adaptivity is provided based on accumulative data gained from observing the user. User modelling, the capturing of information about the ...
Christopher Bailey, Samhaa R. El-Beltagy, Wendy Ha...
WWW
2005
ACM
14 years 8 months ago
Clustering for probabilistic model estimation for CF
Based on the type of collaborative objects, a collaborative filtering (CF) system falls into one of two categories: item-based CF and user-based CF. Clustering is the basic idea i...
Qing Li, Byeong Man Kim, Sung-Hyon Myaeng