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Authors: Junyeob Yim ; Bumsuk Lee and Byung-Yeon Hwang

Affiliation: The Catholic University of Korea, Korea, Republic of

ISBN: 978-989-758-074-1

ISSN: 2184-433X

Keyword(s): Social Network Analysis, Data Mining, Natural Language Processing, Real-time Event-location Analyzer

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Web Information Systems and Technologies ; Web Intelligence

Abstract: A Social Networking Service (SNS) is a web-based platform that helps to build or to keep relationships among people. The SNS platforms in early stage including Friendster and MySpace were implemented for the desktop and laptop users. As more people access wireless internet using their mobile phones, SNS platforms can also have some important features such as “real-time access” and “location information”. These two features make it possible to let people share their activities, interests, and observations in real-time at any places. Recently, most of SNS platforms including Twitter, Facebook, and Yelp use the location information of users. Therefore, if we consider a SNS user as a sensor that reports its observations at a specific location, it would be possible to detect events by analyzing their social contents. There are already numbers of research on this topic have been published or still ongoing. Twitter has been widely used for conducting the research because it has important thr ee features which are required to detect an event: time, location, and content. However, the most approaches struggle with detecting the location which is related to an event correctly. In this paper, we introduce a system that detects an event with its location in real-time based on increment of tweets that mention a specific location frequently. The result of performance evaluation shows that the proposed system detects an event in real-time. We also improved the system performance by reducing some noises from our system. (More)


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Paper citation in several formats:
Yim, J.; Lee, B. and Hwang, B. (2015). Implementation of a Realtime Event-location Analyzer.In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-074-1, ISSN 2184-433X, pages 349-352. DOI: 10.5220/0005193903490352

author={Junyeob Yim. and Bumsuk Lee. and Byung{-}Yeon Hwang.},
title={Implementation of a Realtime Event-location Analyzer},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},


JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Implementation of a Realtime Event-location Analyzer
SN - 978-989-758-074-1
AU - Yim, J.
AU - Lee, B.
AU - Hwang, B.
PY - 2015
SP - 349
EP - 352
DO - 10.5220/0005193903490352

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