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Data Analytics and Management in Data Intensive Domains

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Cover of 'Data Analytics and Management in Data Intensive Domains'

Table of Contents

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    Book Overview
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    Chapter 1 FAIR Principles and Digital Objects: Accelerating Convergence on a Data Infrastructure
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    Chapter 2 Extensible Unifying Data Model Design for Data Integration in FAIR Data Infrastructures
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    Chapter 3 Meaningful Data Reuse in Research Communities
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    Chapter 4 Tabular and Graphic Resources in Quantitative Spectroscopy
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    Chapter 5 The Principles and the Conceptual Architecture of the Metagraph Storage System
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    Chapter 6 Evaluation of Binary Star Formation Models Using Well-Observed Visual Binaries
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    Chapter 7 Proximity Full-Text Search by Means of Additional Indexes with Multi-component Keys: In Pursuit of Optimal Performance
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    Chapter 8 Scope and Challenges of Language Modelling - An Interrogative Survey on Context and Embeddings
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    Chapter 9 Scalable Algorithm for Subsequence Similarity Search in Very Large Time Series Data on Cluster of Phi KNL
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    Chapter 10 Neural Network Approach for Extracting Aggregated Opinions from Analytical Articles
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    Chapter 11 Discovering, Classification, and Localization of Emergency Events via Analyzing of Social Network Text Streams
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    Chapter 12 Citation Content Analysis and a Digital Library
Attention for Chapter 9: Scalable Algorithm for Subsequence Similarity Search in Very Large Time Series Data on Cluster of Phi KNL
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Citations

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Chapter title
Scalable Algorithm for Subsequence Similarity Search in Very Large Time Series Data on Cluster of Phi KNL
Chapter number 9
Book title
Data Analytics and Management in Data Intensive Domains
Published by
Springer, Cham, October 2018
DOI 10.1007/978-3-030-23584-0_9
Book ISBNs
978-3-03-023583-3, 978-3-03-023584-0
Authors

Yana Kraeva, Mikhail Zymbler, Kraeva, Yana, Zymbler, Mikhail

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Professor > Associate Professor 1 33%
Unknown 1 33%
Readers by discipline Count As %
Computer Science 2 67%
Unknown 1 33%

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