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Web Information Systems Engineering – WISE 2018

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Cover of 'Web Information Systems Engineering – WISE 2018'

Table of Contents

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    Book Overview
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    Chapter 1 SARFM: A Sentiment-Aware Review Feature Mapping Approach for Cross-Domain Recommendation
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    Chapter 2 Integrating Collaborative Filtering and Association Rule Mining for Market Basket Recommendation
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    Chapter 3 Unified User and Item Representation Learning for Joint Recommendation in Social Network
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    Chapter 4 Geographical Proximity Boosted Recommendation Algorithms for Real Estate
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    Chapter 5 Cross-domain Recommendation with Consistent Knowledge Transfer by Subspace Alignment
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    Chapter 6 D-ECG: A Dynamic Framework for Cardiac Arrhythmia Detection from IoT-Based ECGs
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    Chapter 7 Jointly Predicting Affective and Mental Health Scores Using Deep Neural Networks of Visual Cues on the Web
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    Chapter 8 Preserving Data Privacy and Security in Australian My Health Record System: A Quality Health Care Implication
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    Chapter 9 A Framework for Processing Cumulative Frequency Queries over Medical Data Streams
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    Chapter 10 Knowledge-Driven Automated Web Service Composition—An EDA-Based Approach
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    Chapter 11 A CP-Net Based Qualitative Composition Approach for an IaaS Provider
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    Chapter 12 LIFE-MP: Online Virtual Machine Consolidation with Multiple Resource Usages in Cloud Environments
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    Chapter 13 Stance and Credibility Based Trust in Social-Sensor Cloud Services
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    Chapter 14 StrDip: A Fast Data Stream Clustering Algorithm Using the Dip Test of Unimodality
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    Chapter 15 Classification and Annotation of Open Internet of Things Datastreams
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    Chapter 16 Efficient Auto-Increment Keys Generation for Distributed Log-Structured Storage Systems
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    Chapter 17 A Parallel Joinless Algorithm for Co-location Pattern Mining Based on Group-Dependent Shard
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    Chapter 18 Improving Maximum Classifier Discrepancy by Considering Joint Distribution for Domain Adaptation
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    Chapter 19 Density Biased Sampling with Locality Sensitive Hashing for Outlier Detection
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    Chapter 20 A Novel Technique of Using Coupled Matrix and Greedy Coordinate Descent for Multi-view Data Representation
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    Chapter 21 Data-Augmented Regression with Generative Convolutional Network
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    Chapter 22 Towards Automatic Complex Feature Engineering
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    Chapter 23 Entity Linking Facing Incomplete Knowledge Base
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    Chapter 24 User Identity Linkage with Accumulated Information from Neighbouring Anchor Links
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    Chapter 25 Mining High-Quality Fine-Grained Type Information from Chinese Online Encyclopedias
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    Chapter 26 Semantics-Enabled Personalised Urban Data Exploration
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    Chapter 27 Recommendation for MOOC with Learner Neighbors and Learning Series
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    Chapter 28 In-depth Exploration of Engagement Patterns in MOOCs
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    Chapter 29 Topic Evolution Models for Long-Running MOOCs
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    Chapter 30 Neuroscientific User Models: The Source of Uncertain User Feedback and Potentials for Improving Web Personalisation
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    Chapter 31 Modeling New and Old Editors’ Behaviors in Different Languages of Wikipedia
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    Chapter 32 A Novel Incremental Dictionary Learning Method for Low Bit Rate Speech Streaming
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    Chapter 33 Identifying Price Index Classes for Electricity Consumers via Dynamic Gradient Boosting
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    Chapter 34 Big Data Exploration for Smart Manufacturing Applications
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    Chapter 35 Dark Web Markets: Turning the Lights on AlphaBay
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Title
Web Information Systems Engineering – WISE 2018
Published by
Springer International Publishing, January 2019
DOI 10.1007/978-3-030-02925-8
ISBNs
978-3-03-002924-1, 978-3-03-002925-8
Editors

Hacid, Hakim, Cellary, Wojciech, Wang, Hua, Paik, Hye-Young, Zhou, Rui

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 14%
Student > Doctoral Student 1 14%
Student > Master 1 14%
Unknown 4 57%
Readers by discipline Count As %
Computer Science 3 43%
Unknown 4 57%