< 국제학술 세미나 개최 안내 >

개최일시 : 2017년 03월 27일 월요일 16:00 ~ 16:50

개최장소 : 백양누리 IBK홀

세미나 제목 : (1) Inference of Social Relationships from Location Data

발표초록 :

For decades, social scientists have been studying people’s social behaviors by utilizing sparse datasets obtained by observations and surveys.  These  studies received a major boost in the past decade due to the availability of web data (e.g., social networks, blogs and review web sites). However, due to the nature of the utilized dataset, these studies were confined to behaviors that were observed mostly in the virtual world. Differing from all the earlier work, here, we aim to study social behaviors by observing people’s behaviors in the real world.  This is now possible due to the availability of large high-resolution spatiotemporal location data collected by GPS-enabled mobile devices through mobile apps (Google’s Map/Navigation/Search/Chrome, Facebook, Foursquare, WhatsApp, Twitter) or through online services, such as geo-tagged contents (tweets from Twitter, pictures from Instagram, Flickr or Google+ Photo), etc.

In particular, we focus on inferring pair-wise strength as the strength of social connections between a pair of users by utilizing the available high-fidelity location data representing people’s movements.

Finally, we argue that due to the sensitivity of location data and user privacy concerns, these inferences cannot be largely carried out on individually contributed data without privacy guarantees. Hence, we discuss open problems in protecting individuals’ location information while enabling these inference analyses.

강연자 : Dr. Cyrus Shahabi / Professor of Computer Science, Electrical Engineering and Spatial Sciences at the University of Southern California (USC)

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개최일시 : 2017년 03월 27일 월요일 17:00 ~ 17:50

개최장소 : 백양누리 IBK홀

세미나 제목 : (2) Effectively Crowdsourcing the Acquisition and Analysis of Geosocial Big Multimedia Data for Disasters

발표초록 :

Efficient and thorough data collection and its timely analysis are critical for disaster response and recovery in order to save people’s lives during disasters. However, access to comprehensive data in disaster areas and their quick analysis to transform the data into actionable knowledge are challenging. With the popularity and pervasiveness of mobile devices, crowdsourcing data collection and analysis has emerged as an effective and scalable solution. This talk addresses the problem of crowdsourcing mobile videos for disasters by identifying two unique challenges of 1) prioritizing visual data collection and transmission under bandwidth scarcity caused by damaged communication networks and 2) analyzing the acquired data in a timely manner. We introduce a new crowdsourcing framework for acquiring and analyzing the mobile videos utilizing fine granularity spatial metadata of videos for a rapidly changing disaster situation. We also develop an analytical model to quantify the visual awareness of a video based on its metadata and propose the visual awareness maximization problem for acquiring the most relevant data under bandwidth constraints. The acquired visual data are effectively distributed to off-site analysts to collectively minimize crowdsourcing efforts for analysis.

강연자 : Dr. Seon Ho Kim / Research Scientist and Associate Director in the Integrated Media Systems Center (IMSC, NSF Engineering Research center) at the University of Southern California (USC)