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1
Representation Learning for Natural Language Processing
Representation Learning for Natural Language Processing
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Representation Learning for Natural Language Processing

ISBN: 9811555729 ;ISBN: 9789811555725 ;EISBN: 9789811555732 ;EISBN: 9811555737 ;DOI: 10.1007/978-981-15-5573-2 ;OCLC: 1176494182

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2
Representation Learning for Natural Language Processing
Representation Learning for Natural Language Processing
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Representation Learning for Natural Language Processing

ISBN: 9789819916009 ;ISBN: 9819916003 ;ISBN: 9819915996 ;ISBN: 9789819915996 ;DOI: 10.1007/978-981-99-1600-9

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3
Clinical Text Mining : Secondary Use of Electronic Patient Records
Clinical Text Mining : Secondary Use of Electronic Patient Records
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Clinical Text Mining : Secondary Use of Electronic Patient Records

https://creativecommons.org/licenses/by/4.0/legalcode ;ISBN: 3319517732 ;ISBN: 9783319517735 ;ISBN: 3319785028 ;ISBN: 9783319785028 ;ISBN: 9783319785035 ;ISBN: 3319785036 ;EISBN: 9783319785035 ;EISBN: 3319785036 ;DOI: 10.1007/978-3-319-78503-5 ;OCLC: OCN: 1036767985 ;OCLC: 1036767985 ;OCLC: 1078960705

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4
Sentiment analysis using product review data
Sentiment analysis using product review data
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Sentiment analysis using product review data

Journal of big data, 2015-06, Vol.2 (1), Article 5 [Peer Reviewed Journal]

Fang and Zhan; licensee Springer. 2015. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ;Journal of Big Data is a copyright of Springer, (2015). All Rights Reserved. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2196-1115 ;EISSN: 2196-1115 ;DOI: 10.1186/s40537-015-0015-2

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5
BioGPT: generative pre-trained transformer for biomedical text generation and mining
BioGPT: generative pre-trained transformer for biomedical text generation and mining
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BioGPT: generative pre-trained transformer for biomedical text generation and mining

Briefings in bioinformatics, 2022-11, Vol.23 (6) [Peer Reviewed Journal]

The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com. ;ISSN: 1467-5463 ;EISSN: 1477-4054 ;DOI: 10.1093/bib/bbac409 ;PMID: 36156661

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6
An overview and empirical comparison of natural language processing (NLP) models and an introduction to and empirical application of autoencoder models in marketing
An overview and empirical comparison of natural language processing (NLP) models and an introduction to and empirical application of autoencoder models in marketing
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An overview and empirical comparison of natural language processing (NLP) models and an introduction to and empirical application of autoencoder models in marketing

Journal of the Academy of Marketing Science, 2022-11, Vol.50 (6), p.1324-1350 [Peer Reviewed Journal]

Academy of Marketing Science 2022 ;COPYRIGHT 2022 Springer ;Academy of Marketing Science 2022. ;ISSN: 0092-0703 ;EISSN: 1552-7824 ;DOI: 10.1007/s11747-022-00840-3

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7
MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports
MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports
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MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports

Scientific data, 2019-12, Vol.6 (1), p.317-8, Article 317 [Peer Reviewed Journal]

2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2019 ;ISSN: 2052-4463 ;EISSN: 2052-4463 ;DOI: 10.1038/s41597-019-0322-0 ;PMID: 31831740

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8
Text data mining of power based on natural language processing technology
Text data mining of power based on natural language processing technology
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Text data mining of power based on natural language processing technology

Journal of physics. Conference series, 2022-05, Vol.2221 (1), p.12050 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;Published under licence by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/2221/1/012050

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9
Named Entity Extraction for Knowledge Graphs: A Literature Overview
Named Entity Extraction for Knowledge Graphs: A Literature Overview
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Named Entity Extraction for Knowledge Graphs: A Literature Overview

IEEE access, 2020, Vol.8, p.32862-32881 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2020.2973928 ;CODEN: IAECCG

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10
Sentiment of Emojis
Sentiment of Emojis
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Sentiment of Emojis

PloS one, 2015-12, Vol.10 (12), p.e0144296-e0144296 [Peer Reviewed Journal]

COPYRIGHT 2015 Public Library of Science ;COPYRIGHT 2015 Public Library of Science ;2015 Kralj Novak et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2015 Kralj Novak et al 2015 Kralj Novak et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0144296 ;PMID: 26641093

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11
Sentiment analysis using deep learning architectures: a review
Sentiment analysis using deep learning architectures: a review
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Sentiment analysis using deep learning architectures: a review

The Artificial intelligence review, 2020-08, Vol.53 (6), p.4335-4385 [Peer Reviewed Journal]

Springer Nature B.V. 2019 ;COPYRIGHT 2020 Springer ;Springer Nature B.V. 2019. ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-019-09794-5

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12
Automatic keyphrase extraction: a survey and trends
Automatic keyphrase extraction: a survey and trends
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Automatic keyphrase extraction: a survey and trends

Journal of intelligent information systems, 2020-04, Vol.54 (2), p.391-424 [Peer Reviewed Journal]

Springer Science+Business Media, LLC, part of Springer Nature 2019 ;Journal of Intelligent Information Systems is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0925-9902 ;EISSN: 1573-7675 ;DOI: 10.1007/s10844-019-00558-9

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13
Text Classification Algorithms: A Survey
Text Classification Algorithms: A Survey
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Text Classification Algorithms: A Survey

Information (Basel), 2019-04, Vol.10 (4), p.150 [Peer Reviewed Journal]

2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2078-2489 ;EISSN: 2078-2489 ;DOI: 10.3390/info10040150

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14
A survey on sentiment analysis methods, applications, and challenges
A survey on sentiment analysis methods, applications, and challenges
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A survey on sentiment analysis methods, applications, and challenges

The Artificial intelligence review, 2022-10, Vol.55 (7), p.5731-5780 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Nature B.V. 2022 ;COPYRIGHT 2022 Springer ;The Author(s), under exclusive licence to Springer Nature B.V. 2022. ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-022-10144-1

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15
A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis
A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis
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A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis

PloS one, 2021-02, Vol.16 (2), p.e0245909-e0245909 [Peer Reviewed Journal]

COPYRIGHT 2021 Public Library of Science ;COPYRIGHT 2021 Public Library of Science ;2021 Rustam et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2021 Rustam et al 2021 Rustam et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0245909 ;PMID: 33630869

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16
Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter
Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter
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Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter

PloS one, 2020-09, Vol.15 (9), p.e0239441-e0239441 [Peer Reviewed Journal]

COPYRIGHT 2020 Public Library of Science ;COPYRIGHT 2020 Public Library of Science ;2020 Xue et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 Xue et al 2020 Xue et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0239441 ;PMID: 32976519

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17
Large-scale automated synthesis of human functional neuroimaging data
Large-scale automated synthesis of human functional neuroimaging data
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Large-scale automated synthesis of human functional neuroimaging data

Nature methods, 2011-08, Vol.8 (8), p.665-670 [Peer Reviewed Journal]

COPYRIGHT 2011 Nature Publishing Group ;Copyright Nature Publishing Group Aug 2011 ;ISSN: 1548-7091 ;EISSN: 1548-7105 ;DOI: 10.1038/nmeth.1635 ;PMID: 21706013

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18
Extracting information from the text of electronic medical records to improve case detection: a systematic review
Extracting information from the text of electronic medical records to improve case detection: a systematic review
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Extracting information from the text of electronic medical records to improve case detection: a systematic review

Journal of the American Medical Informatics Association : JAMIA, 2016-09, Vol.23 (5), p.1007-1015 [Peer Reviewed Journal]

The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. 2016 ;The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. ;ISSN: 1067-5027 ;EISSN: 1527-974X ;DOI: 10.1093/jamia/ocv180 ;PMID: 26911811

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19
State of the art: a review of sentiment analysis based on sequential transfer learning
State of the art: a review of sentiment analysis based on sequential transfer learning
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State of the art: a review of sentiment analysis based on sequential transfer learning

The Artificial intelligence review, 2023, Vol.56 (1), p.749-780 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Nature B.V. 2022 ;COPYRIGHT 2023 Springer ;The Author(s), under exclusive licence to Springer Nature B.V. 2022. ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-022-10183-8

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20
Research on Unstructured Text Data Mining and Fault Classification Based on RNN-LSTM with Malfunction Inspection Report
Research on Unstructured Text Data Mining and Fault Classification Based on RNN-LSTM with Malfunction Inspection Report
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Research on Unstructured Text Data Mining and Fault Classification Based on RNN-LSTM with Malfunction Inspection Report

Energies (Basel), 2017, Vol.10 (3), p.406 [Peer Reviewed Journal]

Copyright MDPI AG 2017 ;ISSN: 1996-1073 ;EISSN: 1996-1073 ;DOI: 10.3390/en10030406

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