Spatio-Temporal Contextualization of Queries for Microtexts in Social Media: Mathematical Modeling

  • Park, Jae-Hong; 
  • Lee, O-Joun; 
  • Han, Joo-Man; 
  • Lee, Eon-Ji; 
  • Jung, Jason J.; 
  • 외 2명
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초록

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. (c) 2017 The Authors. Published by Elsevier B.V.

키워드

Query contextualization; Spatio-temporal contexts; Information fusion
제목
Spatio-Temporal Contextualization of Queries for Microtexts in Social Media: Mathematical Modeling
저자
Park, Jae-Hong; Lee, O-Joun; Han, Joo-Man; Lee, Eon-Ji; Jung, Jason J.; Carratore, Luca; Piccialli, Francesco
DOI
10.1016/j.procs.2017.08.317
발행일
2017-09
유형
Proceedings Paper
저널명
8TH INTERNATIONAL CONFERENCE ON EMERGING UBIQUITOUS SYSTEMS AND PERVASIVE NETWORKS (EUSPN 2017) / 7TH INTERNATIONAL CONFERENCE ON CURRENT AND FUTURE TRENDS OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN HEALTHCARE (ICTH-2017) / AFFILIATED WORKSHOPS
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113
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525 ~ 530