On social event organization
department or school: Science, Faculty of
department or school: Computer Science, Department of
data provider: DSpace
degree campus: UBCV
creator: Li, Keqian
issued: 2016-04-25T20:43:13Z
issued: 2016
related degree: Master of Science - MSc
degree grantor: University of British Columbia
description: Online platforms, such as Meetup and Plancast, have recently become popular for planning gatherings and event organization. However, there is a surprising lack of studies on how to effectively and efficiently organize social events for a large group of people through those platforms. This thesis provides the first systematic study on key computational problem involved in organization of social events. We understand the Social Event Organization problem as assigning a set of events for a group of users to attend, where the users are socially connected with each other and have innate levels of interest in those events. We then introduce a set of formal definition of a restricted version of the problem and show that it is NP-hard and is hard to approximate. We propose efficient heuristic algorithms that improve upon simple greedy algorithms by incorporating the notion of phantom events and by using look-ahead estimation. Using synthetic datasets and three real datasets including those from the platforms Meetup and Plancast, we experimentally demonstrate that our greedy heuristics are scalable and furthermore outperform the baseline algorithms significantly in terms of achieving superior social welfare.
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/57862
note: On Social Event OrganizationbyKeqian LiB. Science, Tsinghua University, 2013A THESIS SUBMITTED IN PARTIAL FULFILLMENTOF THE REQUIREMENTS FOR THE DEGREE OFMaster of ScienceinFACULTY OF GRADUATE AND POSTDOCTORAL STUDIES(Computer Science)The University of British Columbia(Vancouver)April 2016c© Keqian Li, 2016AbstractOnline platforms, such as Meetup and Plancast, have recently become popular forplanning gatherings and event organization. However, there is a surprising lackof studies on how to effectively and efficiently organize social events for a largegroup of people through those platforms. This thesis provides the first systematicstudy on key computational problem involved in organization of social events. Weunderstand the Social Event Organization problem as assigning a set of events fora group of users to attend, where the users are socially connected with each otherand have innate levels of interest in those events. We then introduce a set of formaldefinition of a restricted version of the problem and show that it is NP-hard and ishard to approximate. We propose efficient heuristic algorithms that improve uponsimple greedy algorithms by incorporating the notion of phantom events and by us-ing look-ahead estimation. Using synthetic datasets and three real datasets includ-ing those from the platforms Meetup and Plancast, we experimentally demonstratethat our greedy heuristics are scalable and furthermore outperform the baselinealgorithms significantly in terms of achieving superior social welfare.iiPrefaceThis dissertation is the result of collaborative research based on a publication [17]in the 2014 KDD Conference, a joint work with Prof. Lakshmanan, Dr. Wei Lu,Dr. Smriti Bhagat, Prof. Cong Yu. I developed the theory and conducted theexperiments under their guidance, with the help from them for paper presentationand introducing the problem as constrained optimization problem.iiiTable of ContentsAbstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . …
has type: Thesis/Dissertation
date issued: 2016-05
is shown at: 10.14288/1.0300240
language: eng
degree discipline: Computer Science
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/57862