Projekter pr. år
Abstract
Graphs are ubiquitous and ever-present data structures that have a wide range of applications involving social networks, knowledge bases and biological interactions. The evolution of a graph in such scenarios can yield important insights about the nature and ac- tivities of the underlying network, which can then be utilized for applications such as news dissemination, network monitoring, and content curation. Capturing the continuous evolution of a graph can be achieved by long-standing sub-graph queries. Although, for many applications this can only be achieved by a set of quer- ies, state-of-the-art approaches focus on a single query scenario. In this paper, we therefore introduce the notion of continuous multi-query processing over graph streams and discuss its appli- cation to a number of use cases. To this end, we designed and developed a novel algorithmic solution for efficient multi-query evaluation against a stream of graph updates and experimentally demonstrated its applicability. Our results against two baseline approaches using real-world, as well as synthetic datasets, confirm a two orders of magnitude improvement of the proposed solution.
Originalsprog | Engelsk |
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Titel | Advances in Database Technology - EDBT 2020 : 23rd International Conference on Extending Database Technology, Proceedings |
Redaktører | Angela Bonifati, Yongluan Zhou, Marcos Antonio Vaz Salles, Alexander Bohm, Dan Olteanu, George Fletcher, Arijit Khan, Bin Yang |
Antal sider | 12 |
Forlag | OpenProceedings.org |
Publikationsdato | 2020 |
Sider | 13-24 |
ISBN (Elektronisk) | 978-3-89318-083-7 |
DOI | |
Status | Udgivet - 2020 |
Begivenhed | 23rd International Conference on Extending Database Technology, EDBT 2020 - Copenhagen, Danmark Varighed: 30 mar. 2020 → 2 apr. 2020 |
Konference
Konference | 23rd International Conference on Extending Database Technology, EDBT 2020 |
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Land/Område | Danmark |
By | Copenhagen |
Periode | 30/03/2020 → 02/04/2020 |
Navn | Advances in Database Technology |
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ISSN | 2367-2005 |
Fingeraftryk
Dyk ned i forskningsemnerne om 'Efficient Continuous Multi-Query Processing over Graph Streams'. Sammen danner de et unikt fingeraftryk.-
Poul Due Jensen Professorate in Big Data and Artificial Intelligence
Hose, K., Jendal, T. E. & Hansen, E. R.
01/11/2019 → 31/10/2024
Projekter: Projekt › Forskning
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QWeb: Querying the Web of Data Easily and Efficiently
Hose, K., Montoya, G., Prado, L. A. G. D., Rouces, J., Mathiassen, K. A. M., Zervakis, E. & Setty, V.
01/02/2015 → 31/10/2019
Projekter: Projekt › Forskning