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Advanced Computational Methods for Knowledge Engineering

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Cover of 'Advanced Computational Methods for Knowledge Engineering'

Table of Contents

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    Book Overview
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    Chapter 1 Stochastic DCA for Sparse Multiclass Logistic Regression
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    Chapter 2 Reformulation of the Quadratic Multidimensional Knapsack Problem as Copositive/Completely Positive Prorams
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    Chapter 3 DC Programming and DCA for Enhancing Physical Layer Security in Amplify-and-Forward Relay Beamforming Networks Based on the SNR Approach
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    Chapter 4 A Cash-Flow-Based Optimization Model for Corporate Cash Management: A Monte-Carlo Simulation Approach
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    Chapter 5 Demand Side Management: A Case for Disruptive Behaviour
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    Chapter 6 Enhancing Reduced Order Model Predictive Control for Autonomous Underwater Vehicle
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    Chapter 7 Comparison of Feedback Strategies for Supporting Programming Learning in Integrated Development Environments (IDEs)
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    Chapter 8 Using Online Synchronous Interschool Tournaments to Boost Student Engagement and Learning in Hands-On Physics Lessons
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    Chapter 9 Story-Based Multimedia Analysis Using Social Network Technique
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    Chapter 10 Plot-Creation Support System for Writing Novels
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    Chapter 11 An Improved Algorithm for Mining Top-k Association Rules
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    Chapter 12 A Deep Architecture for Sentiment Analysis of News Articles
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    Chapter 13 Sentiment Polarity Detection in Social Networks: An Approach for Asthma Disease Management
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    Chapter 14 An Overview of Information Discovery Using Latent Semantic Indexing
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    Chapter 15 Similarity Measures for Music Information Retrieval
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    Chapter 16 An Early-Biologisation Process to Improve the Acceptance of Biomimetics in Organizations
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    Chapter 17 Bidirectional Deep Learning of Context Representation for Joint Word Segmentation and POS Tagging
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    Chapter 18 A Model for a Computing Cluster with Two Asynchronous Servers
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    Chapter 19 A Review of Technologies for Conversational Systems
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2 tweeters


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Advanced Computational Methods for Knowledge Engineering
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-61911-8
978-3-31-961910-1, 978-3-31-961911-8

Nguyen-Thinh Le, Tien van Do, Ngoc Thanh Nguyen, Hoai An Le Thi

Twitter Demographics

The data shown below were collected from the profiles of 2 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 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 122 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 12%
Student > Master 14 11%
Student > Bachelor 6 5%
Researcher 3 2%
Lecturer 3 2%
Other 6 5%
Unknown 75 61%
Readers by discipline Count As %
Computer Science 26 21%
Engineering 8 7%
Mathematics 3 2%
Linguistics 2 2%
Business, Management and Accounting 2 2%
Other 5 4%
Unknown 76 62%