Urban Graph Analysis on a Context-driven Querying System

Abstract : Urban computing intends to provide guidance to solve problems in big cities such as pollution, energy consumption, and human mobility. These are, however, difficult problems with several variables interacting in complex patterns. Such complex systems are often represented as graphs, taking advantage of the flexibility of the model and the availability of network science tools for analysis. In this context, expressive query languages capable of tackling graph analysis problems on a customized context are essential. This paper presents a context-driven query system for urban computing where users are responsible for defining their own restrictions over which datalog-like queries are built. Instead of imposing constraints on databases, our goal is to filter consistent data during the query process. Our query language is able to express aggregates in recursive rules, allowing to it capture network properties typical of graph analysis. This paper presents our query system and analyzes its capabilities using use cases in Urban Computing.
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Contributor : Jacques Chabin <>
Submitted on : Thursday, November 8, 2018 - 4:51:25 PM
Last modification on : Thursday, February 7, 2019 - 4:58:25 PM
Document(s) archivé(s) le : Saturday, February 9, 2019 - 2:42:26 PM


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  • HAL Id : hal-01916725, version 1



Jacques Chabin, Luiz Gomes-Jr, Mirian Halfeld-Ferrari. Urban Graph Analysis on a Context-driven Querying System. [Research Report] LIFO, Université d'Orléans. 2018. 〈hal-01916725〉



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