A Fuzzy Low-Dimensional Intersection Graph Representation Approach for Graph Compression and Anonymization

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dc.contributor.author Yamout, Youssef
dc.date.accessioned 2022-06-16T09:12:29Z
dc.date.available 2022-06-16T09:12:29Z
dc.date.copyright 2021 en_US
dc.date.issued 2021-06-23
dc.identifier.uri http://hdl.handle.net/10725/13719
dc.description.abstract The large amount of data represented as a network, or graph, sometimes exceeds the resources of a conventional computing device. In particular, links in a network consume a great portion of memory in comparison to the number of nodes. Even if the graph were to be completely stored on disk with the aid of virtual memory, I/O operations would require exhaustive computing power as opposed to queries that consult the main memory. However, rigorous edge storage is not always necessary to extract useful information and meaningful insights. In this context, we propose a fuzzy lowdimensional representation by mapping any given graph onto a k-dimensional space such that the distance between any two nodes determines their adjacency status. The proposed mapping utilizes an intersection graph representation where k-dimensional balls represent the nodes, and the likelihood of adjacency of two nodes is measured by whether the corresponding balls intersect. The objective is to answer adjacency queries as accurately as possible and to achieve an effective compression. We examine several heuristic algorithms in an attempt to achieve these two main objectives and conduct a thorough experimental analysis providing evidence of the effectiveness of our graph mapping approach. An additional perk of this work is the capability of completely hiding private information in networks. en_US
dc.language.iso en en_US
dc.subject Data compression (Computer science) en_US
dc.subject Pattern recognition systems en_US
dc.subject Graph theory -- Data processing en_US
dc.subject Lebanese American University -- Dissertations en_US
dc.subject Dissertations, Academic en_US
dc.title A Fuzzy Low-Dimensional Intersection Graph Representation Approach for Graph Compression and Anonymization en_US
dc.type Thesis en_US
dc.term.submitted Summer en_US
dc.author.degree MS in Computer Science en_US
dc.author.school SAS en_US
dc.author.idnumber 201501749 en_US
dc.author.commembers Haraty, Ramzi
dc.author.commembers Mansour, Nashat
dc.author.department Computer Science And Mathematics en_US
dc.description.physdesc 1 online resource (x, 45 leaves): ill. (some col.) en_US
dc.author.advisor Abu-Khzam, Faisal
dc.keywords Graph mapping en_US
dc.keywords Data compression en_US
dc.keywords Lossy compression en_US
dc.keywords Intersection graph en_US
dc.keywords Anonymization en_US
dc.description.bibliographiccitations Bibliography: leaf 42-45. en_US
dc.identifier.doi https://doi.org/10.26756/th.2022.195
dc.author.email youssef.yamout@lau.edu en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php en_US
dc.publisher.institution Lebanese American University en_US
dc.author.affiliation Lebanese American University en_US

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