Get Adaptive Multimedia Retrieval: First International Workshop, PDF

By Gareth J. F. Jones (auth.), Andreas Nürnberger, Marcin Detyniecki (eds.)

ISBN-10: 3540221638

ISBN-13: 9783540221630

ISBN-10: 3540259813

ISBN-13: 9783540259817

This publication is a longer selection of contributions that wereoriginally subm- ted to the first overseas Workshop on Adaptive Multimedia Retrieval (AMR 2003), which used to be geared up as a part of the twenty sixth German convention on Arti?cial Intelligence (KI 2003),and held in the course of September 15–18,2003at the collage of Hamburg, Germany. influenced through the final luck of the workshop – as published by means of the stimulating surroundings throughout the workshop and the variety of very and lively members – we ?nally made up our minds to edit a publication in response to revised papers that have been at the start submitted to the workshop. in addition, we invited a few extra introductory contributions with the intention to be capable to offer a conclusive booklet on present themes within the zone of adaptive multimedia retrieval structures. we are hoping that we have been in a position to prepare a stimulating choice of articles for the reader. we love to thank the organizationcommittee of the twenty sixth German convention on Arti?cial Intelligence (KI 2003) for delivering the environment and the admin- trative help in figuring out this workshop as a part of their application. specially, we love to thank Christopher Habel for selling the workshop as a part of the convention application and Andreas Gun ¨ ther for his variety help through the association process.

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Additional resources for Adaptive Multimedia Retrieval: First International Workshop, AMR 2003, Hamburg, Germany, September 15-16, 2003, Revised Selected and Invited Papers

Sample text

A resolver compares the evidence in each component of the user model with data for that component for the Perfect User. The perfect user has Building User Models from Observations 41 attended all of the slides in the course once, for the exact length of the audio. Each component in the user model is given a score based on how close the learner’s listening time compares with that of the perfect user. The final user model data is serialized to XML. SIV then overlays the initial Mecureo-generated ontology with user data.

In the current work, we have been using an online glossary of HCI terms [20] which reflect the material taught in the course. As shown at the top, Mecureo automatically generates the ontologies in the OWL format as we will discuss. This is imported into the main Metasaur interface which is shown as combination of the SIV visualisation of the ontology and the display of the learning object. The teacher who is creating the metadata interacts with this interface. The figure shows the metadata produced at the lower right.

Canonical correlation analysis an overview with application to learning methods. Technical Report CSD-TR-03-02, Royal Holloway University of London (2003) 33. : Image-to-word transformation based on dividing and vector quantizing images with words. In First International Workshop on Multimedia Intelligent Storage and Retrieval Management (MISRM’99) (1999) 34. : Joint image compression and classification with vector quantization and a two dimensional hidden markov model. In: Data Compression Conference.

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Adaptive Multimedia Retrieval: First International Workshop, AMR 2003, Hamburg, Germany, September 15-16, 2003, Revised Selected and Invited Papers by Gareth J. F. Jones (auth.), Andreas Nürnberger, Marcin Detyniecki (eds.)


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