Title: Spatio-Temporal Propagation for Web Sensors

Year of Publication: Dec - 2014
Page Numbers: 69-76
Authors: Shun Hattori
Conference Name: The International Conference on Computer Science, Computer Engineering, and Social Media (CSCESM2014)
- Greece


We experience or forecast various phenomena (e.g., rain, snow, and earthquake) in the physical world, while we carry out various actions (e.g., blogging, searching, and e-shopping) in the Web world. Many researchers have tried to mine the exploding Web world for knowledge about various phenomena and events in the physical world, and also Web services with the Web-mined knowledge have been made available for the public. However, there are few investigations on how accurately Web-mined data reflect physical-world data. It is socially-problematic to utilize Web-mined data in public Web services without ensuring their accuracy sufficiently. The previous papers have introduced “Web Sensors” to extract spatiotemporal numerical values about a physical phenomenon from various kinds of Web documents (e.g., news, blogs, and tweets) searched by linguistic keyword(s) representing the physical phenomenon, and extended Web Sensors with temporal shift and propagation. This paper appends “Spatial Propagation” to Web Sensors, and compares Web sensors with spatial propagation and/or temporal propagation by calculating their correlation coefficients with Japan Meteorological Agency’s physically-sensed spatiotemporal statistics.