| Document Type
|
:
|
BL
|
| Record Number
|
:
|
889913
|
| Main Entry
|
:
|
Venkata Krishna, P.
|
| Title & Author
|
:
|
Social network forensics, cyber security, and machine learning /\ P. Venkata Krishna, [and 2 others].
|
| Publication Statement
|
:
|
Singapore :: Springer,, [2019]
|
| Series Statement
|
:
|
SpringerBriefs in applied sciences and technology : forensic and medical bioinformatics
|
| Page. NO
|
:
|
1 online resource
|
| ISBN
|
:
|
9789811314568
|
|
|
:
|
: 981131456X
|
|
|
:
|
9789811314551
|
|
|
:
|
9811314551
|
| Notes
|
:
|
Working Papers/Technical Papers/Technical Reports
|
| Bibliographies/Indexes
|
:
|
Includes bibliographical references.
|
| Contents
|
:
|
Intro; Contents; 1 Classifying Content Quality and Interaction Quality on Online Social Networks; Abstract; 1.1 Introduction; 1.2 Related Work; 1.3 Analyzing Content Quality in Social Media; 1.3.1 Intrinsic Content Quality; 1.3.2 User Relationships; 1.3.3 Statistics; 1.3.4 Classification; 1.4 Analyzing Interaction Quality in Social Media; 1.4.1 Dataset; 1.4.2 Hypothesis; 1.4.3 Network Analysis; 1.4.4 Classification; 1.5 Conclusion; References; 2 Population Classification upon Dietary Data Using Machine Learning Techniques with IoT and Big Data; Abstract; 2.1 Introduction; 2.1.1 Big Data
|
|
|
:
|
2.1.2 Healthcare and IOT2.1.3 Balanced Versus Unbalanced (Malnutrition) Diet; 2.1.4 The Principle Contributions of This Paper; 2.2 Related Work; 2.3 Proposed Method; 2.3.1 Data Collection and Pre-processing; 2.3.1.1 Targeted Dataset; 2.3.1.2 Loading and Storing of Dataset; 2.3.1.3 Data Pre-processing; 2.3.2 Rule-Based Method for Classification; 2.3.2.1 Classification Techniques Used in PCUDD; 2.4 Experimental Results and Discussion; 2.4.1 Model Performance; 2.4.2 Classification Model Results Comparison; 2.5 Future Work; 2.6 Conclusion; References; 3 Investigating Recommender Systems in OSNs
|
|
|
:
|
4.4 Opinion Mining for Data Analytics4.4.1 Recursive Neural Networks; 4.4.2 Maximum Entropy Method; 4.5 Comparison of Algorithms; 4.6 Proposed Methodology; 4.7 Conclusion and Future Work; References; 5 A Framework for Sentiment Analysis Based Recommender System for Agriculture Using Deep Learning Approach; Abstract; 5.1 Introduction; 5.2 Background; 5.2.1 Lexicon Approach; 5.2.2 Machine Learning Approach; 5.2.3 Hybrid Approach; 5.3 System Model; 5.4 Methodology; 5.4.1 Brief Overview About the Methodology to Perform Sentiment Analysis; 5.4.2 Overall Description; 5.5 Experimental Results
|
|
|
:
|
5.5.1 Andhra Pradesh (AP) Agriculture Tweets Sentiment Rate5.5.2 Unigram Model; 5.5.3 Bigram Model; 5.6 Discussion; 5.7 Conclusion; References; 6 A Review on Crypto-Currency Transactions Using IOTA (Technology); Abstract; 6.1 Introduction; 6.2 Existing Blockchain; 6.2.1 Introduction; 6.2.2 Bitcoin and Its Mining; 6.3 Shortcomings in Blockchains and Bitcoins; 6.4 IOTA; 6.4.1 Introduction; 6.4.2 Directed Acyclic Graph; 6.4.3 Balanced Ternary Logic; 6.4.4 The Tangle; 6.4.5 Issues; 6.5 Summary; 6.6 Conclusion; 6.7 Future Work; Acknowledgements; References; Journal Articles; Technical White Papers
|
|
|
:
|
Abstract3.1 Introduction; 3.2 Analysis of Available Public Data; 3.2.1 System Architecture; 3.2.2 Creating User Profile; 3.3 Facebook Centred High-Quality Filtering (Disadvantages); 3.4 Database System Support: Recommendation Applications; 3.4.1 Creating a Recommender; 3.5 Conclusion; References; 4 A Methodology for Processing Opinion Mining on GST in India from Social Media Data Using Recursive Neural Networks and Maximum Entropy Techniques; Abstract; 4.1 Introduction; 4.2 Social Media Data Analytics; 4.3 Goods and Services Tax (GST) and Its Significance
|
| Abstract
|
:
|
This book discusses the issues and challenges in Online Social Networks (OSNs). It highlights various aspects of OSNs consisting of novel social network strategies and the development of services using different computing models. Moreover, the book investigates how OSNs are impacted by cutting-edge innovations.
|
| Subject
|
:
|
Online social networks-- Technological innovations.
|
| Dewey Classification
|
:
|
006.7/54
|
| LC Classification
|
:
|
HM742.V46 2019
|