ANALYZING SEQUENCE DATA USING NEURAL NETWORKS
Sequence data, such as time series data is analyzed using neural networks, for example, recurrent neural networks. The sequence data is obtained from a source. For example, a sequence data may represent time series data obtained from a sensor. As another example, the sequence of data may represent a...
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Main Authors | , , , , |
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Format | Patent |
Language | English French German |
Published |
17.03.2021
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Subjects | |
Online Access | Get full text |
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Summary: | Sequence data, such as time series data is analyzed using neural networks, for example, recurrent neural networks. The sequence data is obtained from a source. For example, a sequence data may represent time series data obtained from a sensor. As another example, the sequence of data may represent a sequence of user interactions performed by a user with an online system. The sequences of data are provided as input to a neural network. A feature vector representation of each input sequence data is extracted from the neural network. The feature vector representation is used for clustering the sequence data. Salient features of clusters of sequence data are determined. The salient features of clusters of sequence data are provided for display via a user interface. |
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Bibliography: | Application Number: EP20180795244 |