Knowledge computing and its applications : knowledge manipulation and processing techniques.: knowledge manipulation and processing techniques. Volume 1 (2018)

• Record Type: Book
• Further Information: Note: S. Margret Anouncia, Uffe Kock Wiil, editors.
• Editors: Anouncia, S. Margret; Wiil, Uffe Kock
• Contents: Intro; Foreword; Preface; Acknowledgement; Contents; About the Editors; Abbreviations; Knowledge Manipulation Techniques for Internet Technologies; 1 Implementation of Connected Dominating Set in Fog Computing Using Knowledge-Upgraded IoT Devices; Abstract; 1 Introduction; 2 Related Work; 2.1 Homogeneous Networks; 2.2 Heterogeneous Networks; 2.3 Gateway-Based Networks; 3 Gateway-Based Strategic Connected Dominating Set (GWS-CDS); 3.1 Data Structures; 3.2 Construction of Gateway-Based Strategic Connected Dominating Set (GWS-CDS); 4 Simulations and Results; 4.1 Performance Metrics. 4.2 CDS Node Size4.3 CDS Edge Size; 4.4 Average Path Length (APL); 5 Conclusion; Acknowledgement; References; 2 Developing Security Intelligence in Big Data; Abstract; 1 Introduction of Big Data Security; 2 Big Data Architecture Vulnerabilities (www.cisoplatform.com); 2.1 Existing Big Data Architecture; 3 Big Data Security Techniques; 4 Threats and Attacks Against Big Data; 5 Case Study of CIAâ#x80;#x94;USA Documents Disclosed on WikiLeaks; 6 Big Data Security Analytics Tools; 7 Open Source Security Tools for Big Data; 8 Summary; References; 3 Methods to Investigate Concept Drift in Big Data Streams. Abstract1 Introduction; 1.1 Social Media Analysis; 1.2 Applications of Social Media Analysis; 1.3 Introduction to Streaming Data; 1.4 General Architecture of Clustering Streaming Data; 1.5 Introduction to Concept Drift; 1.5.1 Types of Concept Drift; 1.5.2 Need to Detect Concept Drift in Streaming Data; 2 Literature Review; 2.1 Clustering Categorical Streaming Data; 2.2 Detecting Concept Drift in Categorical/Textual Data Streams; 2.3 Research Done for Detecting Concept Drift on Social Media; 3 Proposed Framework for Detecting Concept Drift on Social Media; 3.1 Proposed Framework; 4 Conclusion. 4.4 The CKS-Based NB Classifier5 Enhanced Sentiment Detection with CKS-Sentiment Mining Algorithm; 6 CKS-Based Enhanced Tweet Interpretation: Experiments and Results; 6.1 Experimentâ#x80;#x94;CKS-Based Semantic Classification; 6.2 Experimentâ#x80;#x94;Enhanced Sentiment Mining with Distance-Based CKS-Sentiment Mining Algorithm; 7 Conclusion and Future Scope; References; 5 Workload Assessment for a Sustainable Manufacturing Paradigm Using Social Network Analysis Method; Abstract; 1 Introduction; 2 Problem Description; 3 Framework of the Proposed Dynamic Workload Adjustment; 4 Experimentation.
• Publisher Details: Singapore : Springer
• Publication Date: 2018
• Extent: 1 online resource (xxi, 293 pages), illustrations
• Subjects: 006.3/3; Expert systems (Computer science); Big data; Internet of things; COMPUTERS -- General; Big data; Expert systems (Computer science); Internet of things; Computer Science; Information Systems Applications (incl. Internet); Computational Intelligence; Artificial Intelligence (incl. Robotics); Electronic books; Electronic book
• Languages: English
• ISBNs: 9789811066801; 9811066809
• Related ISBNs: 9789811066795; 9811066795
• Notes: Note: Includes bibliographical references.; Note: Online resource; title from PDF title page (EBSCO, viewed February 19, 2018).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.