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Knowledge Discovery, Knowledge Engineering and Knowledge Management

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Cover of 'Knowledge Discovery, Knowledge Engineering and Knowledge Management'

Table of Contents

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    Book Overview
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    Chapter 1 Secure Outsourced k NN Data Classification over Encrypted Data Using Secure Chain Distance Matrices
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    Chapter 2 HCC-Learn Framework for Hybrid Learning in Recommender Systems
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    Chapter 3 Analysis and Detection of Unreliable Users in Twitter: Two Case Studies
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    Chapter 4 An Environment to Model Massive Open Online Course Dynamics
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    Chapter 5 An Advanced Driver Assistance Test Cases Generation Methodology Based on Highway Traffic Situation Description Ontologies
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    Chapter 6 Reasoning over Ontologies with DLV
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    Chapter 7 Machine Learning-Assisted Cognition of Driving Context and Avoidance of Road Obstacles
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    Chapter 8 The Evaluation of Ontologies for Quality, Suitability for Reuse, and the Significant Role of Social Factors
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    Chapter 9 Towards a Term Clustering Framework for Modular Ontology Learning
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    Chapter 10 A Semantic Approach to Constraint-Based Reasoning in Geographical Domains
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    Chapter 11 DHPs: Dependency Hearst’s Patterns for Hypernym Relation Extraction
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    Chapter 12 Investigating Knowledge Management Within Small and Medium-Sized Companies: The Proof of Concept Results of a Survey Addressed to Software Development Industry
Attention for Chapter 3: Analysis and Detection of Unreliable Users in Twitter: Two Case Studies
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Citations

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Chapter title
Analysis and Detection of Unreliable Users in Twitter: Two Case Studies
Chapter number 3
Book title
Knowledge Discovery, Knowledge Engineering and Knowledge Management
Published by
Springer, Cham, September 2018
DOI 10.1007/978-3-030-49559-6_3
Book ISBNs
978-3-03-049558-9, 978-3-03-049559-6
Authors

Nuno Guimaraes, Alvaro Figueira, Luis Torgo, Guimaraes, Nuno, Figueira, Alvaro, Torgo, Luis

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 25%
Researcher 2 25%
Professor 1 13%
Unknown 3 38%
Readers by discipline Count As %
Computer Science 4 50%
Engineering 1 13%
Unknown 3 38%

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