Show simple item record

dc.contributor.authorZhang, Chuxu
dc.contributor.authorYu, Lu
dc.contributor.authorLiu, Chuang
dc.contributor.authorZhang, Zi-Ke
dc.contributor.authorZhou, Tao
dc.date.accessioned2018-01-15T06:35:08Z
dc.date.available2018-01-15T06:35:08Z
dc.date.issued2017-08-03
dc.identifier.citationZhang C, Yu L, Liu C, Zhang Z-K, Zhou T (2017) A Community-Aware Approach to Minimizing Dissemination in Graphs. Lecture Notes in Computer Science: 85–99. Available: http://dx.doi.org/10.1007/978-3-319-63579-8_8.
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.doi10.1007/978-3-319-63579-8_8
dc.identifier.urihttp://hdl.handle.net/10754/626774
dc.description.abstractGiven a graph, can we minimize the spread of an entity (such as a meme or a virus) while maintaining the graph’s community structure (defined as groups of nodes with denser intra-connectivity than inter-connectivity)? At first glance, these two objectives seem at odds with each other. To minimize dissemination, nodes or links are often deleted to reduce the graph’s connectivity. These deletions can (and often do) destroy the graph’s community structure, which is an important construct in real-world settings (e.g., communities promote trust among their members). We utilize rewiring of links to achieve both objectives. Examples of rewiring in real life are prevalent, such as purchasing products from a new farm since the local farm has signs of mad cow disease; getting information from a new source after a disaster since your usual source is no longer available, etc. Our community-aware approach, called constrCRlink (short for Constraint Community Relink), preserves (on average) 98.6% of the efficacy of the best community-agnostic link-deletion approach (namely, NetMelt+), but changes the original community structure of the graph by only 4.5%. In contrast, NetMelt+ changes 13.6% of the original community structure.
dc.description.sponsorshipThis work was partially supported by Natural Science Foundation of China (Grant Nos. 61673151, 61503110 and 61433014), Zhejiang Provincial Natural Science Foundation of China (Grant Nos. LY14A050001 and LQ16F030006).
dc.publisherSpringer Nature
dc.relation.urlhttps://link.springer.com/chapter/10.1007%2F978-3-319-63579-8_8
dc.subjectCommunity structure
dc.subjectDissemination control in graph
dc.subjectGraph mining
dc.titleA Community-Aware Approach to Minimizing Dissemination in Graphs
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentComputer Science Program
dc.identifier.journalLecture Notes in Computer Science
dc.conference.date2017-07-07 to 2017-07-09
dc.conference.name1st Asia-Pacific Web and Web-Age Information Management Joint Conference on Web and Big Data, APWeb-WAIM 2017
dc.conference.locationBeijing, CHN
dc.contributor.institutionDepartment of Computer Science and Engineering, University of Notre Dame, Notre Dame, United States
dc.contributor.institutionAlibaba Research Center for Complexity Sciences, Hangzhou Normal University, Hangzhou, China
dc.contributor.institutionBig Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
kaust.personYu, Lu
dc.date.published-online2017-08-03
dc.date.published-print2017


This item appears in the following Collection(s)

Show simple item record