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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Bibliographic Details
Main Authors SAFFAR, Mohammad, NGUYEN, Christopher, CHI, Nhan Vu Lam, HAN, Binh, TRINH, Anh H
Format Patent
LanguageEnglish
French
German
Published 17.03.2021
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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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.
Bibliography:Application Number: EP20180795244