Principles of Big Graph: In-depth Insight, Volume 128 in the Advances in Computer series, highlights new advances in the field with this new volume presenting interesting chapters on a variety of topics, including CESDAM: Centered subgraph data matrix for large graph representation, Bivariate, cluster and suitability analysis of NoSQL Solutions for big graph applications, An 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, and An investigation on socio-cyber crime graph.
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Preface
Ripon Patgiri, Ganesh ChandraDeka and Anupam Biswas
1. CESDAM: Centered subgraph data matrix for large graph representation
Anupam Biswas and Bhaskar Biswas
2. Bivariate, cluster and suitability analysis of NoSQL Solutions for big graph applications
Samiya Khan, Xiufeng Liu, Syed Arshad Ali and Mansaf Alam
3. An empirical investigation on BigGraph using deep learning
Lilapati Waikhom and Ripon Patgiri
4. Analyzing correlation between quality and accuracy of graph clustering
Soumita Das and Anupam Biswas
5. geneBF: Filtering protein-coded gene graph data using bloom filter
Sabuzima Nayak and Ripon Patgiri
6. Processing large graphs with an alternative representation
Ravi Kishore Devarapalli and Anupam Biswas
7. MapReduce based convolutional graph neural networks: A comprehensive review
U. Kartheek Chandra Patnaik and Ripon Patgiri
8. Fast exact triangle counting in large graphs using SIMD acceleration
Kaushik Ravichandran, Akshara Subramaniasivam, Aishwarya PS and Kumar NS
9. A comprehensive investigation on attack graphs
M Franckie Singha and Ripon Patgiri
10. Qubit representation of a binary tree and its operations in quantum computation
Arnab Roy, Joseph L Pachuau and Anish Kumar Saha
11. Modified ML-KNN: Role of similarity measures and nearest neighbor configuration in multi label text classification on big social network graph data
Saurabh Kumar Srivastava, Ankit Vidyarthi and Sandeep Kumar Singh
12. Big graph based online learning through social networks
Rahul Chandra Kushwaha
13. Community detection in large-scale real-world networks
Dhananjay Kumar Singh and Prasenjit Choudhury
14. Power rank: An interactive web page ranking algorithm
Ankit Vidyarthi and Pawan Singh
15. GA based energy efficient modelling of a wireless sensor network
Anish Kumar Saha, Joseph L Pachuau, Arnab Roy and C. T. Bhunia
16. The major challenges of big graph and their solutions: A review
Fitsum Gebreegziabher and Ripon Patgiri
17. An investigation on socio-cyber crime graph
V S NageswaraRao Kadiyala and Ripon Patgiri
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Edited by some of the best scientists in the field, this series presents the latest updates in the field of computers
Provides an update on the issues and challenges faced by current researchers
Updates on future research agendas
Includes advanced topics for intensive research for researchers
Produktdetaljer
ISBN
9780323898102
Publisert
2023-01-26
Utgiver
Vendor
Academic Press Inc
Vekt
860 gr
Høyde
229 mm
Bredde
152 mm
Aldersnivå
P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
458