Title	Mining Large-scale Networks
Creator	Koutra, Danai
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2016-08-30T09:00
Description	Graphs naturally represent information in a wide range of disciplines, from social science to biology and transportation engineering. These graphs often span millions or even billions of nodes and interactions between them. Within this deluge of interconnected data, how can we extract useful knowledge, understand the underlying processes, and make interesting discoveries This tutorial will focus on fundamental problems in large-scale graph mining including ranking, clustering and community detection, summarization, similarity, alignment, pattern discovery, and anomaly detection. It will also present challenges and open problems, and invite discussion of how some of these may be addressed by combining network science with the power of crowds.
Extent	37.0
Subject	Mathematics; Game theory, economics, social and behavioral sciences; Computer science; Applied computer science
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: University of Michigan
Series	BIRS Workshop Lecture Videos (Oaxaca de Juárez (Mexico))
Date Available	2019-03-05
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0376630
URI	http://hdl.handle.net/2429/68483
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Faculty
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

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Mining Large-scale Networks Koutra, Danai

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