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Data Science – Analytics and Applications

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Cover of 'Data Science – Analytics and Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Circadian Cycles and Work Under Pressure: A Stochastic Process Model for E-learning Population Dynamics
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    Chapter 2 Investigating and Forecasting User Activities in Newsblogs: A Study of Seasonality, Volatility and Attention Burst
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    Chapter 3 Knowledge-Based Short-Term Load-Forecasting for Maritime Container Terminals
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    Chapter 4 Beyond Spectral Clustering: A Comparative Study of Community Detection for Document Clustering
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    Chapter 5 Third Party Effect: Community Based Spreading in Complex Networks
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    Chapter 6 Cosine Approximate Nearest Neighbors
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    Chapter 7 Information Extraction Engine for Sentiment-Topic Matching in Product Intelligence Applications
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    Chapter 8 Towards German Word Embeddings: A Use Case with Predictive Sentiment Analysis
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    Chapter 9 Feature Extraction and Large Activity-Set Recognition Using Mobile Phone Sensors
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    Chapter 10 The Choice of Metric for Clustering of Electrical Power Distribution Consumers
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    Chapter 11 Evolution of the Bitcoin Address Graph
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    Chapter 12 A Reference Architecture for Quality Improvement in Steel Production
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    Chapter 13 Anomaly Detection and Structural Analysis in Industrial Production Environments
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    Chapter 14 Semantically Annotated Manufacturing Data to support Decision Making in Industry 4.0: A Use-Case Driven Approach
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    Chapter 15 Improving Maintenance Processes with Data Science
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    Chapter 16 ouRframe
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    Chapter 17 Sentiment Analysis
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Title
Data Science – Analytics and Applications
Published by
Springer Vieweg, Wiesbaden, January 2017
DOI 10.1007/978-3-658-19287-7
ISBNs
978-3-65-819286-0, 978-3-65-819287-7
Editors

Peter Haber, Thomas Lampoltshammer, Manfred Mayr

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 33%
Student > Ph. D. Student 1 11%
Student > Doctoral Student 1 11%
Student > Master 1 11%
Unknown 3 33%
Readers by discipline Count As %
Computer Science 3 33%
Arts and Humanities 1 11%
Agricultural and Biological Sciences 1 11%
Engineering 1 11%
Unknown 3 33%