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...

Full description

Saved in:
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
Online AccessGet full text

Cover

Abstract 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.
AbstractList 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.
Author SAFFAR, Mohammad
HAN, Binh
TRINH, Anh H
NGUYEN, Christopher
CHI, Nhan Vu Lam
Author_xml – fullname: SAFFAR, Mohammad
– fullname: NGUYEN, Christopher
– fullname: CHI, Nhan Vu Lam
– fullname: HAN, Binh
– fullname: TRINH, Anh H
BookMark eNrjYmDJy89L5WTQdfRz9ImM8vRzVwh2DQx19XN2VXBxDHFUCA0Gifm5hgY5-gCpkHD_IO9gHgbWtMSc4lReKM3NoODmGuLsoZtakB-fWlyQmJyal1oS7xpgbGZoaWZi6WhiTIQSAHgBJxY
ContentType Patent
DBID EVB
DatabaseName esp@cenet
DatabaseTitleList
Database_xml – sequence: 1
  dbid: EVB
  name: esp@cenet
  url: http://worldwide.espacenet.com/singleLineSearch?locale=en_EP
  sourceTypes: Open Access Repository
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
Chemistry
Sciences
Physics
DocumentTitleAlternate ANALYSE DE DONNÉES DE SÉQUENCES À L'AIDE DE RÉSEAUX NEURONAUX
ANALYSE VON SEQUENZDATEN UNTER VERWENDUNG NEURONALER NETZWERKE
ExternalDocumentID EP3619649A4
GroupedDBID EVB
ID FETCH-epo_espacenet_EP3619649A43
IEDL.DBID EVB
IngestDate Fri Jul 19 14:30:28 EDT 2024
IsOpenAccess true
IsPeerReviewed false
IsScholarly false
Language English
French
German
LinkModel DirectLink
MergedId FETCHMERGED-epo_espacenet_EP3619649A43
Notes Application Number: EP20180795244
OpenAccessLink https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210317&DB=EPODOC&CC=EP&NR=3619649A4
ParticipantIDs epo_espacenet_EP3619649A4
PublicationCentury 2000
PublicationDate 20210317
PublicationDateYYYYMMDD 2021-03-17
PublicationDate_xml – month: 03
  year: 2021
  text: 20210317
  day: 17
PublicationDecade 2020
PublicationYear 2021
RelatedCompanies Arimo, LLC
RelatedCompanies_xml – name: Arimo, LLC
Score 3.3269038
Snippet 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....
SourceID epo
SourceType Open Access Repository
SubjectTerms CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
Title ANALYZING SEQUENCE DATA USING NEURAL NETWORKS
URI https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210317&DB=EPODOC&locale=&CC=EP&NR=3619649A4
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfR3LToNAcFLr86aosb7CwXAjBruAHIihQFu1BaSgrZeG5ZH0QhvB-PvObmj1oqfdzCaT2Ulm57HzALgpEg2VDi1kkhBNJoVhyFQhKasCUZSiSGjO67jHnjaMydNUnbZgsa6F4X1Cv3hzRJSoFOW95u_16ieI5fDcyuqWLhC0fOhHpiM13vEdG1qgS07PdAPf8W3JtnEneaHZ1VjnKcMiW7DNrGjWZt997bGilNVvjdI_hJ0AkZX1EbTyUoB9ez14TYC9cfPfLcAuT9BMKwQ2Qlgdg2x51mj2_ugNxIn7ErMYkehYkSWyERoD0XPj0BrhEr354fPkBMS-G9lDGSmYb247d4MNrd1TaJfLMj8Dkd7TDG0lFMmkIKh2qaEnKjo7WYYGDsnVDnT-RHP-z9kFHDC2sawqRb-Edv3xmV-hmq3pNWfQN94pfJA
link.rule.ids 230,309,786,891,25594,76903
linkProvider European Patent Office
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfR3LTsJAcIL4wJtWjfjswfTWmMrS2gMxpS0PKVuEouCFdPtIuBRia_x9ZzcFvehpN7PJZHaS2XnsPADu0lBHpcNSlYREV0lqmirTSMSrQDQtTUOWiDruIdV7U_I8a84qsNzUwog-oV-iOSJKVITyXoj3ev0TxHJEbmV-z5YIWj11gpajlN7xAx9aYChOu-WOfMe3FdvGnULHrYbOO0-ZFtmBXQM9QuEpvbZ5Ucr6t0bpHMHeCJFlxTFUkkyCmr0ZvCbBwbD875ZgXyRoRjkCSyHMT0C1qOXN3_u0K0_clymPEcmOFVgyH6HRlak7HVseLsGbPx5MTkHuuIHdU5GCxfa2C3e0pbVxBtVslSXnILNHFqOthCIZpgTVLjONsInOThyjgUOSZh3qf6K5-OfsFmq9YOgtvD4dXMIhZyHPsNKMK6gWH5_JNarcgt0IZn0D1h9_eg
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Apatent&rft.title=ANALYZING+SEQUENCE+DATA+USING+NEURAL+NETWORKS&rft.inventor=SAFFAR%2C+Mohammad&rft.inventor=NGUYEN%2C+Christopher&rft.inventor=CHI%2C+Nhan+Vu+Lam&rft.inventor=HAN%2C+Binh&rft.inventor=TRINH%2C+Anh+H&rft.date=2021-03-17&rft.externalDBID=A4&rft.externalDocID=EP3619649A4