Principles of Big Graph: In-depth Insight: Volume 128
Published on 26. January 2023
Book
Hardback
458 pages
978-0-323-89810-2 (ISBN)
Description
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.
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.
More details
Series
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Elsevier Science & Technology
Target group
Professional and scholarly
Database Architects, Consultants, Administrators, Big Data Professionals, Data Scientists, Database management researchers and students.
Dimensions
Height: 229 mm
Width: 152 mm
Weight
860 gr
ISBN-13
978-0-323-89810-2 (9780323898102)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Persons
Dr. Ripon Patgiri is an Assistant Professor at the Department of Computer Science & Engineering, National Institute of Technology Silchar, since 2013. His research interests include bloom filters, storage systems, security, and cryptography computing. He has published numerous papers in reputed journals, conferences, and books. Also, he has been awarded with several international patents. He is a senior member of IEEE. He was the General Chair of ICACNI 2018 and BigDML 2019. He is the Organizing Chair of FRSM 2020 and ADCOM 2020. Also, he is the Program Chair of CoMSO 2020, CoMSO 2021, and CoMSO 2022. He is also an editor of several multi-authored books. Moreover, he has received two research project fundings from SERB and DST, India. Ganesh Chandra Deka is currently Deputy Director (Training) at Directorate General of Training, Ministry of Skill Development and Entrepreneurship, Government of India, New Delhi-110001, India. His research interests include e-Governance, Big Data Analytics, NoSQL Databases and Vocational Education and Training.
He has 2 books on Cloud Computing published by LAP Lambert, Germany. He is the Co-author for 4 text books on Fundamentals of Computer Science (3 books published by Moni Manik Prakashan, Guwahati, Assam, India and 1 IGI Global, USA). As of now he has edited 14 books (6 IGI Global, USA, 5 CRC Press, USA, 2 Elsevier & 1 Springer) on Big data, NoSQL and Cloud Computing and authored 10 Book Chapters.
He has published around 47 research papers in various IEEE conferences. He has organized 08 IEEE International Conferences as Technical Chair in India. He is the Member of the editorial board and reviewer for various Journals and International conferences. Member of IEEE, the Institution of Electronics and Telecommunication Engineers, India and Associate Member, the Institution of Engineers, India Assistant Professor Anupam Biswas works in Computer Science and Engineering at the National Institute of Technology Silchar, Silchar, Assam, India.
He has 2 books on Cloud Computing published by LAP Lambert, Germany. He is the Co-author for 4 text books on Fundamentals of Computer Science (3 books published by Moni Manik Prakashan, Guwahati, Assam, India and 1 IGI Global, USA). As of now he has edited 14 books (6 IGI Global, USA, 5 CRC Press, USA, 2 Elsevier & 1 Springer) on Big data, NoSQL and Cloud Computing and authored 10 Book Chapters.
He has published around 47 research papers in various IEEE conferences. He has organized 08 IEEE International Conferences as Technical Chair in India. He is the Member of the editorial board and reviewer for various Journals and International conferences. Member of IEEE, the Institution of Electronics and Telecommunication Engineers, India and Associate Member, the Institution of Engineers, India Assistant Professor Anupam Biswas works in Computer Science and Engineering at the National Institute of Technology Silchar, Silchar, Assam, India.
Volume editor
Assistant Professor, Department of Computer Science and Engineering, National Institute of Technology, Silchar, India
Ministry of Skill Development and Entrepreneurship, New Delhi, India
Assistant Professor, Computer Science and Engineering, National Institute of Technology Silchar, Silchar, Assam, India
Content
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
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