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MDATA: A New Knowledge Representation Model

Overview of attention for book
Cover of 'MDATA: A New Knowledge Representation Model'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction to the MDATA Model
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    Chapter 2 The Framework of the MDATA Computing Model
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    Chapter 3 Spatiotemporal Data Cleaning and Knowledge Fusion
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    Chapter 4 Chinese Named Entity Recognition: Applications and Challenges
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    Chapter 5 Joint Extraction of Entities and Relations: An Advanced BERT-based Decomposition Method
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    Chapter 6 Entity Alignment: Optimization by Seed Selection
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    Chapter 7 Knowledge Extraction: Automatic Classification of Matching Rules
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    Chapter 8 Network Embedding Attack: An Euclidean Distance Based Method
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    Chapter 9 Few-Shot Knowledge Reasoning: An Attention Mechanism Based Method
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    Chapter 10 Applications of Knowledge Representation Learning
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    Chapter 11 Detection and Defense Methods of Cyber Attacks
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    Chapter 12 A Distributed Framework for APT Attack Analysis
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    Chapter 13 Social Unrest Events Prediction by Contextual Gated Graph Convolutional Networks
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    Chapter 14 Information Cascading in Social Networks
Attention for Chapter 4: Chinese Named Entity Recognition: Applications and Challenges
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Citations

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Chapter title
Chinese Named Entity Recognition: Applications and Challenges
Chapter number 4
Book title
MDATA: A New Knowledge Representation Model
Published by
Springer, Cham, January 2021
DOI 10.1007/978-3-030-71590-8_4
Book ISBNs
978-3-03-071589-2, 978-3-03-071590-8
Authors

Xi, Qisen, Ren, Yizhi, Yao, Siyu, Wu, Guohua, Miao, Gongxun, Zhang, Zhen

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 25%
Student > Doctoral Student 1 25%
Student > Master 1 25%
Unknown 1 25%
Readers by discipline Count As %
Computer Science 2 50%
Unknown 2 50%

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