Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4960761 | Procedia Computer Science | 2017 | 6 Pages |
Abstract
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.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Jae-Hong Park, O-Joun Lee, Joo-Man Han, Eon-Ji Lee, Jason J. Jung, Luca Carratore, Francesco Piccialli,