| Bibliography | Zweigle, Oliver; Häussermann, Kai; Käppeler, Uwe-Philipp; Levi, Paul: Extended TA Algorithm for adapting a Situation Ontology.
In: Proceedings of the FIRA RoboWorld Congress 2009, Progress in Robotics.
University of Stuttgart : Collaborative Research Center SFB 627 (Nexus: World Models for Mobile Context-Based Systems).
Communications in Computer and Information Science; 44, pp. 364-371, english.
Incheon, Korea: Springer Verlag, August 18, 2009.
ISBN: 978-3-642-03985-0.
Article in Proceedings (Conference Paper).
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| Corporation | Federation of International Robot-soccer Association |
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| CR-Schema | I.2.6 (Artificial Intelligence Learning)
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| Keywords | situation recognition, situation, bayes |
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| Abstract | In this work we introduce an improved version of a learning algorithm for the automatic adaption of a situation ontology (TAA) which extends the basic principle of the learning algorithm. The approach bases on the assumption of uncertain data and includes elements from the domain of Bayesian Networks and Machine Learning. It is embedded into the cluster of excellence Nexus at the University of Stuttgart which has the aim to build a distributed context aware system for sharing context data.
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Full text and
other links | Springerlink
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| Department(s) | University of Stuttgart, Institute of Parallel and Distributed Systems, Image Understanding
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| Project(s) | SFB-627, C3 (University of Stuttgart, Institute of Parallel and Distributed Systems, Image Understanding)
SFB-627, E3 (University of Stuttgart, Institute of Parallel and Distributed Systems, Image Understanding)
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| Entry date | September 28, 2009 |
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