User Modelling as an Application of Actors

Author(s):  
Ani Nenkova ◽  
Galia Angelova
Keyword(s):  
2003 ◽  
Author(s):  
Eugene Santos ◽  
Hien Nguyen ◽  
Qunhua Zhao ◽  
Hua Wang

Author(s):  
Sahan Bulathwela ◽  
María Pérez-Ortiz ◽  
Rishabh Mehrotra ◽  
Davor Orlic ◽  
Colin de la Higuera ◽  
...  
Keyword(s):  

Author(s):  
A. Silva ◽  
L. Faria ◽  
Z. Vale ◽  
C. Ramos ◽  
A. Marques

2012 ◽  
pp. 281-304
Author(s):  
Pradipta Biswas ◽  
Pat Langdon

2004 ◽  
Vol 19 (1) ◽  
pp. 61-88 ◽  
Author(s):  
MARTIN E. MÜLLER

Machine learning seems to offer the solution to many problems in user modelling. However, one tends to run into similar problems each time one tries to apply out-of-the-box solutions to machine learning. This article closely relates the user modelling problem to the machine learning problem. It explicates some inherent dilemmas that are likely to be overlooked when applying machine learning algorithms in user modelling. Some examples illustrate how specific approaches deliver satisfying results and discuss underlying assumptions on the domain or how learned hypotheses relate to the requirements on the user model. Finally, some new or underestimated approaches offering promising perspectives in combined systems are discussed. The article concludes with a tentative ‘‘checklist” that one might like to consider when planning to apply machine learning to user modelling techniques.


Author(s):  
Ronny Cook ◽  
Judy Kay ◽  
Bob Kummerfeld
Keyword(s):  

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