Title: Deflection Analysis for Spatially Propagated Web Sensors

Year of Publication: Jan - 2015
Page Numbers: 20-28
Authors: Shun Hattori
Conference Name: The International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC2015)
- United Arab Emirates


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 researches have tried to mine the Web for knowledge about various phenomena in the physical world, and also Web services with Web-mined knowledge have been made available for the public. However, there are not enough 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 work has introduced various kinds of “Web Sensors” with Temporal Shift and Spatio-Temporal Propagation to extract spatiotemporal numerical data about a targeted physical phenomenon from Web documents searched by linguistic keyword(s) representing the physical phenomenon, and compared them based on their correlation coefficients with Japan Meteorological Agency’s physically-sensed spatiotemporal statistics. To analyze the deflection of Spatially-Propagated Web Sensors, this paper introduces their novel definition based on not only distance but also azimuthal angle between geographic spaces.