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Big Data Applications and Services 2017

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Cover of 'Big Data Applications and Services 2017'

Table of Contents

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    Book Overview
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    Chapter 1 3D Volume Visualization System Based on GPUs for Medical Big Data
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    Chapter 2 A Fire Flame Simulation Scheme with Massively Parallel Processing
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    Chapter 3 A Framework for Calculating Damages of Personal Information Leakage Accidents
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    Chapter 4 A Hierarchical Structure for Representing 3D Respiration Organ Models
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    Chapter 5 An Effective Method for Detecting Outlying Regions in a 2-Dimensional Array
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    Chapter 6 An Effective Recall-Oriented Information Retrieval System Evaluation
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    Chapter 7 Chentry: Automated Evaluation of Students’ Learning Progress for Entry Education Software
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    Chapter 8 Constrained Big Data Mining in an Edge Computing Environment
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    Chapter 9 Constrained Frequent Pattern Mining from Big Data Via Crowdsourcing
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    Chapter 10 Data-Driven Prediction of Ship Destinations in the Harbor Area Using Deep Learning
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    Chapter 11 Design and Implementation of a Sunshine Duration Calculation System with Massively Parallel Processing
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    Chapter 12 Developing 3D Annotation Features for 3D Digital Textbooks
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    Chapter 13 Efficient Mining of Time Interval-Based Association Rules
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    Chapter 14 Investigating the Role of Musical Genre in Human Perception of Music Stretching Resistance
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    Chapter 15 Keyword-Based Metadata Modeling for Experimental Omics Data Dissemination
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    Chapter 16 Nonlinear Time-series Mining of Social Influence
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    Chapter 17 PEGASEF: A Provenance-Based Big Data Service Framework for Efficient Simulation Execution on Shared Computing Clusters
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    Chapter 18 Preference-Aware Music Recommendation Using Song Lyrics
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    Chapter 19 Real-Time Smart Safe-Return-Home Service Based on Big Data Analytics
Attention for Chapter 18: Preference-Aware Music Recommendation Using Song Lyrics
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Chapter title
Preference-Aware Music Recommendation Using Song Lyrics
Chapter number 18
Book title
Big Data Applications and Services 2017
Published by
Springer, Singapore, August 2017
DOI 10.1007/978-981-13-0695-2_18
Book ISBNs
978-9-81-130694-5, 978-9-81-130695-2
Authors

Sein Jang, Battulga Lkhagvadorj, Aziz Nasridinov, Jang, Sein, Lkhagvadorj, Battulga, Nasridinov, Aziz

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 67%
Unknown 2 33%
Readers by discipline Count As %
Computer Science 2 33%
Arts and Humanities 1 17%
Unknown 3 50%