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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 Three Simple Approaches to Combining Neural Networks with Algorithms
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    Chapter 2 Methodology for Automated Identifying Food Export Potential
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    Chapter 3 Integration of the JINR Hybrid Computing Resources with the DIRAC Interware for Data Intensive Applications
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    Chapter 4 On Information Search Measures and Metrics Within Integration of Information Systems on Inorganic Substances Properties
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    Chapter 5 Models Are Functioning in Scenarios
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    Chapter 6 Applied Ontologies for Managing Graphic Resources in Quantitative Spectroscopy
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    Chapter 7 Realization of Different Techniques for Anomaly Detection in Astronomical Databases
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    Chapter 8 Modern Astronomical Surveys for Parameterization of Stars and Interstellar Medium
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    Chapter 9 Searching for Optical Counterparts of LIGO/Virgo Events in O2 Run
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    Chapter 10 Google Books Ngram: Problems of Representativeness and Data Reliability
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    Chapter 11 Method for Expert Search Using Topical Similarity of Documents
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    Chapter 12 Depression Detection from Social Media Profiles
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    Chapter 13 Tatar WordNet: The Sources and the Component Parts
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    Chapter 14 An Approach to Fuzzy Clustering of Big Data Inside a Parallel Relational DBMS
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    Chapter 15 Issues and Lessons Learned in the Development of Academic Study Programs in Data Science
Attention for Chapter 2: Methodology for Automated Identifying Food Export Potential
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Citations

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Chapter title
Methodology for Automated Identifying Food Export Potential
Chapter number 2
Book title
Data Analytics and Management in Data Intensive Domains
Published by
Springer, Cham, October 2019
DOI 10.1007/978-3-030-51913-1_2
Book ISBNs
978-3-03-051912-4, 978-3-03-051913-1
Authors

Dmitry Devyatkin, Yulia Otmakhova, Devyatkin, Dmitry, Otmakhova, Yulia

View on publisher site
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 %
Lecturer 1 33%
Other 1 33%
Student > Master 1 33%
Readers by discipline Count As %
Economics, Econometrics and Finance 2 67%
Computer Science 1 33%

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