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On the application of Big Data in future large-scale intelligent Smart City installations.

, , , , and . Int. J. Pervasive Comput. Commun., 10 (2): 168-182 (2014)

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Using DynamoGraph: application scenarios for large-scale temporal graph processing., and . iiWAS, page 76:1-76:5. ACM, (2015)Making Computers Understand Coalition and Opposition in Parliamentary Democracy., , and . EGOV, volume 9820 of Lecture Notes in Computer Science, page 265-276. Springer, (2016)Big Data in Large Scale Intelligent Smart City Installations., , , , and . iiWAS, page 428. ACM, (2013)Building an on-demand virtual computing market in non-commercial communities., , and . SAC, page 351-356. ACM, (2013)Using Big Data for Emotionally Intelligent Mobile Services through Multi-Modal Emotion Recognition., , , and . ICOST, volume 9102 of Lecture Notes in Computer Science, page 127-138. Springer, (2015)DynamoGraph: extending the Pregel paradigm for large-scale temporal graph processing., and . Int. J. Grid Util. Comput., 7 (2): 141-151 (2016)DynamoGraph: A Distributed System for Large-scale, Temporal Graph Processing, its Implementation and First Observations., and . WWW (Companion Volume), page 861-866. ACM, (2016)Take a Penny, Leave a Penny - Scaling out to Off-premise Unused Cloud Resources., and . GI-Jahrestagung, volume P-220 of LNI, page 3063-3076. GI, (2013)Towards Cloud-Based Distributed Scaleable Processing over Large-Scale Temporal Graphs., and . WETICE, page 143-148. IEEE Computer Society, (2014)Platform for General-Purpose Distributed Data-Mining on Large Dynamic Graphs., and . WETICE, page 178-183. IEEE Computer Society, (2013)