Opening book details…
Can I read Massive Graph Analytics (Chapman & Hall/CRC Data Science Series) on EtoBox?
Massive Graph Analytics (Chapman & Hall/CRC Data Science Series) by BARDERS,DAVID. A. is a business book available to read on EtoBox.
What is Massive Graph Analytics (Chapman & Hall/CRC Data Science Series) about?
A work-efficient parallel breadth-first search algorithm (or how to cope with the nondeterminism of reducers) / Charles E. Leiserson and Tao B. Schardl -- Multi-objective shortest paths / Stephan Erb, Moritz Kobitzsch, Lawrence Mandow, and Peter Sanders -- Multicore algorithms for graph connectivity problems / George M. Slota, Sivasankaran Rajamanickam, and Kamesh Madduri -- Distributed memory parallel algorithms for massive graphs / Maksudul Alam, Shaikh Arifuzzaman, Hasanuzzaman Bhuiyan, Maleq
Who reads Massive Graph Analytics (Chapman & Hall/CRC Data Science Series)?
It is typically read by working professionals who need an authoritative practice reference.
Common subject areas: medicine, law, business, engineering.
- Author
- BARDERS,DAVID. A.
- Publisher
- CRC Press, Taylor & Francis Group
- Published
- 2022
- Language
- EN
- ISBN
- 9781032169231
- Category
- business
- Subjects
- Business, Programming, Mathematics
- Updated
- 2026-03-25
More by BARDERS,DAVID. A.
Browse all works by BARDERS,DAVID. A.
Similar books
- JavaScript for Data Science (Chapman & Hall/CRC Data Science Series) — Cambridge, Maya Gans, Toby Hodges, Greg Wilson (2020)
- Statistical Foundations of Data Science (Chapman & Hall/CRC Data Science Series) — Jianqing Fan, Runze Li, Cun-Hui Zhang, Hui Zou (2020)
- Data Science: A First Introduction (Chapman & Hall/CRC Data Science Series) — Tiffany Timbers, Trevor Campbell and Melissa Lee (2022)
- Frontiers in Data Science (Chapman & Hall/CRC Big Data Series) — Matthias Dehmer, Frank Emmert-Streib (2018)
- Data Science and Analytics with Python (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) — Jesús Rogel-Salazar (2017)
- Data Science for Sensory and Consumer Scientists (Chapman & Hall/CRC Data Science Series) — Thierry Worch, Julien Delarue, Vanessa Rios De Souza, John M. Ennis (2023)