Data driven network construction and analysis extending the functionality of netdriller

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dc.contributor.advisorAlhajj, Reda
dc.contributor.authorSarraf Shirazi, Atieh
dc.date.accessioned2017-12-18T22:37:00Z
dc.date.available2017-12-18T22:37:00Z
dc.date.issued2012
dc.descriptionBibliography: p. 78-84en
dc.descriptionA few pages are in colour.en
dc.description.abstractSocial network analysis has emerged as a technique in sociology. However, it has become more and more interesting to researchers of other fields. The flexibility and scalability supported by the new technology encouraged the extension of the social network technology to handle new applications. A social network is defined as a set of nodes and a set of links connecting them. Social network analysis is the task of analyzing a social network with the purpose of gaining some information about the network such as patterns of connection or important nodes. However, there are a lot of applications where only raw data is available. Usually, the data sets contain data objects with their set of features. In this work, we propose an approach to construct a social network fom a raw data set. The approach is based on the assumption that if two objects are similar, there is a higher probability that they are placed in the same cluster in different clustering solutions. Based on this assumption, we use a multi-objective genetic algorithm approach to find different solutions for partitioning the data objects. The actors of the final social network are the data objects, and the link between them shows the ratio of partitioning solutions that the objects are placed in the same cluster. This work is implemented in NetDriller, a powerful social network analysis tool developed at Data Mining group at the University of Calgary. We show the validity of our approach by evaluating both the intermediate clustering results and the constructed social network in a case study on stock market.
dc.format.extentvi, 84 leaves : ill. ; 30 cm.en
dc.identifier.citationSarraf Shirazi, A. (2012). Data driven network construction and analysis extending the functionality of netdriller (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/5027en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/5027
dc.identifier.urihttp://hdl.handle.net/1880/106028
dc.language.isoeng
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.titleData driven network construction and analysis extending the functionality of netdriller
dc.typemaster thesis
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
ucalgary.thesis.accessionTheses Collection 58.002:Box 2118 627942988
ucalgary.thesis.notesUARCen
ucalgary.thesis.uarcreleaseyen
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