Hadath: From Social Media Mapping to Multi-Resolution Event-Enriched Maps
March 05, 2020 Β· Declared Dead Β· π ACS/IEEE International Conference on Computer Systems and Applications
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Authors
Faizan Ur Rehman, Imad Afyouni, Ahmed Lbath, Saleh Basalamah
arXiv ID
2003.02615
Category
cs.IR: Information Retrieval
Cross-listed
cs.DB,
cs.SI
Citations
1
Venue
ACS/IEEE International Conference on Computer Systems and Applications
Last Checked
4 months ago
Abstract
Publicly available data is increasing rapidly, and will continue to grow with the advancement of technologies in sensors, smartphones and the Internet of Things. Data from multiple sources can improve coverage and provide more relevant knowledge about surrounding events and points of Interest. The strength of one source of data can compensate for the shortcomings of another source by providing supplementary information. Maps are also getting popular day-by-day and people are using it to achieve their daily task smoothly and efficiently. Starting from paper maps hundred years ago, multiple type of maps are available with point of interest, real-time traffic update or displaying micro-blogs from social media. In this paper, we introduce Hadath, a system that displays multi-resolution live events of interest from a variety of available data sources. The system has been designed to be able to handle multiple type of inputs by encapsulating incoming unstructured data into generic data packets. System extracts local events of interest from generic data packets and identify their spatio-temporal scope to display such events on a map, so that as a user changes the zoom level, only events of appropriate scope are displayed. This allows us to show live events in correspondence to the scale of view - when viewing at a city scale, we see events of higher significance, while zooming in to a neighbourhood, events of a more local interest are highlighted. The final output creates a unique and dynamic map browsing experience. Finally, to validate our proposed system, we conducted experiments on social media data.
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