Spatio-Temporal Contextualization of Queries for Microtexts in Social Media: Mathematical Modeling
Jae-Hong Park, O‐Joun Lee, Jooman Han, Eon-Ji Lee, Jason J. Jung, Luca Carratore, Francesco Piccialli · Procedia Computer Science · 2017
In this paper, we present our ongoing project on query contextualization by integrating all possible IoT-based data sources. Most importantly, mobile users are regarded as the IoT sensors which can be the textual data sources with spatio-temporal contexts. Given a large amount of text streams, it has been difficult for the traditional information retrieval systems to conduct the searching tasks. The goal of this work is i ) to understand and process microtexts in social media (e.g., Twitter and Facebook), and ii ) to reformulate the queries for searching for relevant microtexts in these social media.