Spatio-Temporal Contextualization of Queries for Microtexts in Social Media: Mathematical Modeling
| Autor: | Joo-Man Han, Jason J. Jung, Luca Carratore, Jae-Hong Park, O-Joun Lee, Francesco Piccialli, Eon-Ji Lee |
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| Přispěvatelé: | Park, J. -H., Lee, O. -J., Han, J. -M., Lee, E. -J., Jung, J. J., Carratore, Luca, Piccialli, F. |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Contextualization Information retrieval Computer science business.industry Process (engineering) Query contextualization 02 engineering and technology Spatio-temporal contexts 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences 020201 artificial intelligence & image processing Social media Information fusion Internet of Things business General Environmental Science |
| Zdroj: | EUSPN/ICTH |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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