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. Peer-review under responsibility of the Conference Program Chairs.
| Original language | English |
|---|---|
| Pages (from-to) | 525-530 |
| Number of pages | 6 |
| Journal | Procedia Computer Science |
| Volume | 113 |
| DOIs | |
| State | Published - 2017 |
| Event | 8th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, EUSPN 2017 and the 7th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, ICTH 2017 - Lund, Sweden Duration: 18 Sep 2017 → 20 Sep 2017 |
Bibliographical note
Funding Information:This research was supported by the MISP (Ministry of Science, ICT & Future Planning), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP (Institute for Information & communications Technology Promotion).
Publisher Copyright:
© 2017 The Authors. Published by Elsevier B.V.
Keywords
- Information fusion
- Query contextualization
- Spatio-temporal contexts