Title：Efficient Detection of Emergency Event from Moving Object Data Streams

Speaker：Limin Guo

Time：10:00-11:00, November 19th, 2013, Tuesday

Venue: Lecture Room No. 334, 3rd Floor, Building #5, Institute of Software, Chinese Academy of Sciences.

Abstract：The advance of positioning technology enables us to online collect moving object data streams for many applications. One of the most significant applications is to detect emergency event through observed abnormal behavior of objects for disaster prediction. However, the continuously generated moving object data streams are often accumulated to a massive dataset in a few seconds and thus challenge existing data analysis techniques. In this talk, we model a process of emergency event forming as a process of rolling a snowball, that is, we compare a size-rapidly-changed group of moving objects to a snowball. Thus, the problem of emergency event detection can be resovled by snowball discovery. Then, we will present a new moving object pattern—snowball. Further we will study the discovery of snowballs and present two novel algorithms.

Biography: Dr. Limin Guo is an assistant professor in Institute of Software Chinese Academy of Sciences. Her research interests include database research and implementation, data mining on moving objects.