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In building effective interfaces or computer human interaction devices, a main limitation of traditional presentation design is the inability to meet individual user expectation at run-time. On-line design of individualised presentations that surpass the limits of the ”one size fits all” approaches can be made possible by user modeling techniques. Building models of users can be done throughMachine Learning, but this requires techniques that are specific to the task.One particular issue is that the user models cannot remain static, in the sense that during the use of the intended interaction more knowledge can be gathered which should in turn be used to improve the user models. The knowledge from which the construction of the models can be made is many-fold: web logs, speech, images...
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Lectures
Context changes detection by one-class svms
Feb 25, 2007
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Automatically building domain model in hypermedia applications
Feb 25, 2007
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Building and Employing Probabilistic User Models
Feb 25, 2007
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Activity modelling using email and web page classification
Feb 25, 2007
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Log pre-processing and grammatical inference for Web usage mining
Feb 25, 2007
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First order logic for learning user models in the semantic web: why do we need i...
Feb 25, 2007
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Improving Infoville XXI using Machine Learning Techniques
Feb 25, 2007
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User models from implicit feedback for proactive information retrieval
Feb 25, 2007
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5975 Views
Chronological Sampling for Email Filtering
Feb 25, 2007
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3114 Views