Data, Engineering and Applications: Volume 1

Data, Engineering and Applications: Volume 1
Data, Engineering and Applications: Volume 1
By 作者: Rajesh Kumar Shukla
ISBN-10 书号: 9811363463
ISBN-13 书号: 9789811363467
Edition 版本: 1st ed. 2019
Release Finelybook 出版日期: 2019-03-19
pages 页数: (191 )


Book Description to Finelybook sorting

This book presents a compilation of current trends, technologies, and challenges in connection with Big Data. Many fields of science and engineering are data-driven, or generate huge amounts of data that are ripe for the picking. There are now more sources of data than ever before, and more means of capturing data. At the same time, the sheer volume and complexity of the data have sparked new developments, where many Big Data problems require new solutions.
Given its scope, the book offers a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of Big Data applications.
Front Matter
Part 1. On Data Mining and Social Networking
A Review of Recommender System and Related Dimensions
Collaborative Filtering Techniques in Recommendation Systems
Predicting Users’ Interest Through ELM-Based Collaborative Filtering
Application of Community Detection Technique in Text Mining
Sentiment Analysis on WhatsApp Group Chat Using R
A Recent Survey on Information-Hiding Techniques
Investigation of Feature Selection Techniques on Performance of Automatic Text Categorization
Identification and Analysis of Future User Interactions Using Some Link Prediction Methods in Social Networks
Sentiment Prediction of Facebook Status Updates of Youngsters
Part ll. On Machine Learning
Logistic Regression for the Diagnosis of Cervical Cancer
Automatic Examination Timetable Scheduling Using Particle Swarm Optimization and Local Search Algorithm
Personality Trait Identification for Written Texts Using MLNB
Deep Neural Network Compression via Knowledge Distillation for Embedded Vision Applications
An Elective Course Decision Support System Using Decision Tree and Fuzzy Logic
An Appearance-Based Gender Classification Using Radon Features
An Automatic Text Summarization on Naive Bayes Classifier Using Latent Semantic Analysis
Preserving Patient Records with Biometrics Ildentification in e-Health Systems


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