Kemafor Anyanwu
Affiliations: | Computer Science | North Carolina State University, Raleigh, NC |
Area:
Computer ScienceGoogle:
"Kemafor Anyanwu"Children
Sign in to add traineeHaizhou Fu | grad student | 2014 | NCSU |
Padmashree Ravindra | grad student | 2014 | NCSU |
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Publications
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Ravindra P, Anyanwu K. (2015) Scaling unbound-property queries on Big RDF data warehouses using MapReduce Edbt 2015 - 18th International Conference On Extending Database Technology, Proceedings. 169-180 |
Ravindra P, Kim H, Anyanwu K. (2015) Rewriting complex SPARQL analytical queries for efficient cloud-based processing Proceedings - 2015 Ieee International Conference On Big Data, Ieee Big Data 2015. 32-37 |
Ravindra P, Anyanwu K. (2014) Nesting strategies for enabling nimble MapReduce dataflows for large RDF data International Journal On Semantic Web and Information Systems. 10: 1-26 |
Ravindra P, Anyanwu K. (2014) Towards optimization of RDF analytical queries on MapReduce Proceedings - International Conference On Data Engineering. 335-339 |
Sessoms M, Anyanwu K. (2014) Enabling a Package Query Paradigm on the Semantic Web: Model and Algorithms Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8420: 1-32 |
Kim HS, Ravindra P, Anyanwu K. (2014) A semantics-oriented storage model for big heterogeneous RDF data Ceur Workshop Proceedings. 1272: 437-440 |
Anyanwu K, Kim H, Ravindra P. (2013) Algebraic optimization for processing graph pattern queries in the cloud Ieee Internet Computing. 17: 52-61 |
Anyanwu K. (2013) A vision for SPARQL multi-query optimization on MapReduce Proceedings - International Conference On Data Engineering. 25-26 |
Kim H, Anyanwu K. (2013) Optimizing queries over semantically integrated datasets on MapReduce platforms Proceedings - 2013 Ieee International Conference On Big Data, Big Data 2013. 5-6 |
Fu H, Kim H, Anyanwu K. (2013) Scaling concurrency of personalized Semantic search over Large RDF data Proceedings - 2013 Ieee International Conference On Big Data, Big Data 2013. 556-562 |