Principles of Big Graph: In-depth Insight

The book Principles of Big Graph: In-depth Insight, Volume 128 in the Advances in Computer series, highlights new advances in the field, including CESDAM, Bivariate, cluster, and suitability analysis of NoSQL Solutions for big graph applications, empirical investigation on Big Graph using deep learning, Analyzing correlation between quality and accuracy of graph clustering, geneBF: Filtering protein-coded gene graph data using bloom filter, Processing large graphs with an alternative representation, MapReduce based convolutional graph neural networks: A comprehensive review, fast exact triangle counting in large graphs using SIMD acceleration, comprehensive investigation on attack graphs, Qubit representation of a binary tree and its operations in quantum computation, Modified ML-KNN: Role of similarity measures and nearest neighbor configuration in multi-label text classification on big social network graph data, big graph-based online learning through social networks, community detection in large-scale real-world networks, power rank: An interactive web page ranking algorithm, GA-based energy-efficient modelling of a wireless sensor network, and an investigation on socio-cyber crime graph.

Format: Hardback
Length: 458 pages
Publication date: 01 February 2023
Publisher: Elsevier Science & Technology

Principles of Big Graph: In-depth Insight,Volume 128 in the Advances in Computer series, presents a comprehensive exploration of the latest advancements in the field. This new volume offers a diverse range of captivating chapters on various topics, including:

CESDAM: Centered Subgraph Data Matrix for Large Graph Representation
Bivariate, Cluster, and Suitability Analysis of NoSQL Solutions for Big Graph Applications
Empirical Investigation on Big Graph Using Deep Learning
Analyzing Correlation Between Quality and Accuracy of Graph Clustering
GeneBF: Filtering Protein-Coded Gene Graph Data Using Bloom Filter
Processing Large Graphs with an Alternative Representation
MapReduce-Based Convolutional Graph Neural Networks: A Comprehensive Review
Fast Exact Triangle Counting in Large Graphs Using SIMD Acceleration
A Comprehensive Investigation on Attack Graphs
Qubit Representation of a Binary Tree and Its Operations in Quantum Computation
Modified ML-KNN: Role of Similarity Measures and Nearest Neighbor Configuration in Multi-Label Text Classification on Big Social Network Graph Data
Big Graph-Based Online Learning Through Social Networks
Community Detection in Large-Scale Real-World Networks
Power Rank: An Interactive Web Page Ranking Algorithm
GA-Based Energy Efficient Modelling of a Wireless Sensor Network
The Major Challenges of Big Graph and Their Solutions: A Review
An Investigation on Socio-Cyber Crime Graph

These chapters delve into the cutting-edge research and applications of big graph technology, providing valuable insights for researchers, practitioners, and enthusiasts alike. The book serves as a valuable resource for anyone seeking to stay updated with the latest developments in this rapidly evolving field.

Dimension: 229 x 152 (mm)
ISBN-13: 9780323898102