Adaptive Event Recognition with the use of Limited Training Data
Abstract: This paper presents a novel event recognition system, which is capable of adapting itself to improve its performance on a small set of training data. The event recognition system is represented by a network of events, related to each other by temporal constraints. This symbolic representat...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.335.9008 2023-05-15T16:36:01+02:00 Adaptive Event Recognition with the use of Limited Training Data Georgios Paliouras David S. Brée The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.335.9008 http://users.iit.demokritos.gr/~paliourg/papers/CSC98.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.335.9008 http://users.iit.demokritos.gr/~paliourg/papers/CSC98.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://users.iit.demokritos.gr/~paliourg/papers/CSC98.pdf learning adaptive systems event recognition network models text ftciteseerx 2016-09-11T00:10:52Z Abstract: This paper presents a novel event recognition system, which is capable of adapting itself to improve its performance on a small set of training data. The event recognition system is represented by a network of events, related to each other by temporal constraints. This symbolic representation is particularly suitable to the treatment of overlapping events, which have been overlooked in most of the work on event recognition. Additionally, a method for refining the temporal parameters of the recognition system is presented here. The method uses a small set of preclassified training examples to improve the performance of the system. The principle of minimal model change is used to overcome the sparseness of the training data. Particular emphasis is given to the issue of multiple positive examples, which is prevalent when allowing overlapping events. The new system has been applied to the thematic analysis of humpback whale songs with encouraging results. Text Humpback Whale Unknown |
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English |
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learning adaptive systems event recognition network models |
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learning adaptive systems event recognition network models Georgios Paliouras David S. Brée Adaptive Event Recognition with the use of Limited Training Data |
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learning adaptive systems event recognition network models |
description |
Abstract: This paper presents a novel event recognition system, which is capable of adapting itself to improve its performance on a small set of training data. The event recognition system is represented by a network of events, related to each other by temporal constraints. This symbolic representation is particularly suitable to the treatment of overlapping events, which have been overlooked in most of the work on event recognition. Additionally, a method for refining the temporal parameters of the recognition system is presented here. The method uses a small set of preclassified training examples to improve the performance of the system. The principle of minimal model change is used to overcome the sparseness of the training data. Particular emphasis is given to the issue of multiple positive examples, which is prevalent when allowing overlapping events. The new system has been applied to the thematic analysis of humpback whale songs with encouraging results. |
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The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Georgios Paliouras David S. Brée |
author_facet |
Georgios Paliouras David S. Brée |
author_sort |
Georgios Paliouras |
title |
Adaptive Event Recognition with the use of Limited Training Data |
title_short |
Adaptive Event Recognition with the use of Limited Training Data |
title_full |
Adaptive Event Recognition with the use of Limited Training Data |
title_fullStr |
Adaptive Event Recognition with the use of Limited Training Data |
title_full_unstemmed |
Adaptive Event Recognition with the use of Limited Training Data |
title_sort |
adaptive event recognition with the use of limited training data |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.335.9008 http://users.iit.demokritos.gr/~paliourg/papers/CSC98.pdf |
genre |
Humpback Whale |
genre_facet |
Humpback Whale |
op_source |
http://users.iit.demokritos.gr/~paliourg/papers/CSC98.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.335.9008 http://users.iit.demokritos.gr/~paliourg/papers/CSC98.pdf |
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Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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