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Machine Intelligence and Big Data in Industry

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Cover of 'Machine Intelligence and Big Data in Industry'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Automatic Sentiment Analysis in Polish Language
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    Chapter 2 Learning Curve with Machine Translation Based on Parallel, Bilingual Corpora
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    Chapter 3 N-Gram Collection from a Large-Scale Corpus of Polish Internet
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    Chapter 4 Study Fields Clustering Using KRK Competences
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    Chapter 5 Semantic Textual Similarity Using Various Approaches
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    Chapter 6 Identification of Diabetes Disease Using Committees of Neural Network-Based Classifiers
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    Chapter 7 Enzyme Function Classification Based on Borda Count Ranking Aggregation Method
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    Chapter 8 Mining of Frequent Action Rules
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    Chapter 9 Automatic Translation of Multi-word Labels
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    Chapter 10 VTLN Using Different Warping Functions for Template Matching
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    Chapter 11 A Comparative Study on Music Genre Classification Algorithms
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    Chapter 12 Information Selection and Data Compression RapidMiner Library
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    Chapter 13 Automatic Clustering Methods of Offers in an E-Commerce Marketplace
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    Chapter 14 Application of Machine Learning Algorithms for Bitcoin Automated Trading
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    Chapter 15 Maximal Discernibility Discretization of Attributes—A FPGA Approach
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    Chapter 16 Big Data Solutions for Smart Grids and Smart Meters
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    Chapter 17 Intelligent System of Limited Resource Allocation for Large-Scale Agent Systems
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    Chapter 18 Searching for Logical Patterns in Multi-sensor Data from the Industrial Internet
Attention for Chapter 14: Application of Machine Learning Algorithms for Bitcoin Automated Trading
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Citations

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Chapter title
Application of Machine Learning Algorithms for Bitcoin Automated Trading
Chapter number 14
Book title
Machine Intelligence and Big Data in Industry
Published by
Springer International Publishing, March 2016
DOI 10.1007/978-3-319-30315-4_14
Book ISBNs
978-3-31-930314-7, 978-3-31-930315-4
Authors

Kamil Żbikowski

Editors

Dominik Ryżko, Piotr Gawrysiak, Marzena Kryszkiewicz, Henryk Rybiński

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 3%
Unknown 31 97%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 25%
Researcher 6 19%
Student > Ph. D. Student 4 13%
Student > Master 4 13%
Lecturer 3 9%
Other 3 9%
Unknown 4 13%
Readers by discipline Count As %
Computer Science 18 56%
Engineering 4 13%
Mathematics 2 6%
Social Sciences 2 6%
Linguistics 1 3%
Other 1 3%
Unknown 4 13%