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Published in IEEE Big Data, 2016
This paper introduces GraphFlow framework for processing big graphs using Galaxy and Apache Spark.
Recommended citation: S. Riazi and B. Norris, GraphFlow: Workflow-Based Big Graph Processing, In Proc. of 2016 IEEE International Conference on Big Data (Big Data), 2016. https://hpcl.cs.uoregon.edu/pubs/biggraphs16.pdf
Published in IEEE Big Data, 2018
This paper introduces novel algorithms for computing SSSP over very large dynamic graphs using a vertex-centric approach.
Recommended citation: S. Riazi, S. Srinivasan, S. K. Das, S. Bhowmick and B. Norris, Single-Source Shortest Path Tree for Big Dynamic Graphs, 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, USA, 2018, pp. 4054-4062. http://sarariazi.github.io/files/sssp.pdf
Published in IEEE DataCom, 2019
This paper introduces VCNE, a network embedding approach for very large graphs.
Recommended citation: S. Riazi and B. Norris. Distributed-memory vertex-centric network embedding for large-scale graphs. Proceedings of the 2019 IEEE 5th International Conference on Big Data Intelligence and Computing (DATACOM), Taiwan, 2019 http://sarariazi.github.io/files/vcne.pdf
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Database Systems, , 2022
This is a part of the Normalization topic. These lectures assume students know how to create Entity-Relationship Diagrams (ERDs) from the requirements and how to map the ERD to relational schema.