PPT-A New Framework for Criteria-based Trajectory Segmentatio

Author : giovanna-bartolotta | Published Date : 2016-07-20

Kevin Buchin Joint work with Sander Alewijnse Maike Buchin Andrea Kölzsch Helmut Kruckenberg and Michel Westenberg September 30 2013 Stopovers in Geese

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A New Framework for Criteria-based Trajectory Segmentatio: Transcript

Kevin Buchin Joint work with Sander Alewijnse Maike Buchin Andrea Kölzsch Helmut Kruckenberg and Michel Westenberg September 30 2013 Stopovers in Geese Migration . ca Mario A Nascimento Department of Computing Science University of Alberta Canada marionascimentoualbertaca ABSTRACT Trajectory clustering is the process of grouping similar tr a jectories according to a similarity distance Several meth ods for traj A proposed tool to support development and management of NAMAs . Marcos Castro. Climate Change Group, World Bank. . UNFCCC Regional Workshop on CDM and NAMAs for Latin America and the Caribbean. 31 August – 2 September, Bogota, Colombia. Road. . Networks. Renchu . Song, . . Weiwei . Sun, . . Fudan. University. Baihua Zheng, Singapore Management University. . Yu . Zheng, . Microsoft Research, . Beijing. Background. Big Data. Huge volume of spatial trajectories cause heavy burden to data storage and data process. Useful Concepts and tools. C. Antonio Sánchez. Dept of Elec & Comp Eng. University of British Columbia. Vancouver, BC, Canada. antonios@ece.ubc.ca. Siavash Khallaghi. Dept of Elec & Comp Eng. -based Learning from Demonstration. Anthony Dubis. “. Keyframe. -based Learning from Demonstration – Method and Evaluation” . – . Akgun. , . Cakmak. , Jiang, and . Thomaz. What We’ll Cover. : Trajectory Classification Using Hierarchical Region-Based and Trajectory-Based Clustering. Jae-Gil Lee, . Jiawei. Han, . Xiaolei. Li, Hector Gonzalez. University of Illinois at Urbana-Champaign. VLDB 2008. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER . GRAPHICS, . DECEMBER 2012. Authors:. . Christian . Tominski. Heidrun. Schumann. Gennady . Andrienko. Natalia . Andrienko. BY:. Farah . Kamw. Introduction. . USING HIERARHICAL REGION-BASED . . AND . . TRAJECTORY-BASED CLUSTERING . . JaeGil. Lee, . Jiawei. Han, . . Xiaolei. . Li, . Hector Gonzalez. Department of Computer Science. CS587x Lecture. Department of Computer Science. Iowa State University. Location-based Services (LBS) . Dilemma. To use an LBS, a user needs to disclose her location, but a person’s whereabouts may imply sensitive private information. Decision-making and planning. Spring 2018. CS 599.. Instructor: Jyo Deshmukh. Decision-making hierarchy. Motion planning. Overview. 2. Decision-making hierarchy. 3. Route Planning. Behavioral Planning. Jie Bao, . Ruiyuan. Li, . Xiuwen. Yi, Yu Zheng. Urban Computing Group. Microsoft Research, China. Motivation. Bridge the gap between . massive. . trajectory data. and . urban computing applications. Group-Based Trajectories for the analysis of observational cohorts Michael W. Plankey, PhD Professor Georgetown University Medical Center Washington, DC, USA 7,087 Men who have sex with Men (MSM) enrolled in Fly and trajectory scans Tim Mooney 2/27/2015 Fly-scan choices Software fly scan Data acquired while positioners move at constant speed Detectors triggered by software Periodically, or at user-specified time intervals Chi-Yin Chow. Department of Computer Science. City University of Hong Kong. Mohamed F. Mokbel. Department of Computer Science and Engineering. University of Minnesota . Outline. Introduction. Protecting Trajectory Privacy in Location-based Services.

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