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Employing Probabilistic Matching Algorithms for Identity Management in the Telecommunication Industry

dc.contributor.authorOdedina, Omolade Temitope
dc.description.abstractThe telecommunication industry has a lot of data related to households, individuals and devices. Advertisers pay a premium to ensure they advertise to their target audience. To ensure that content is personalized, it is necessary to accurately predict who is using a device in real time. A probabilistic matching algorithm to determine the profile of an individual based on behavioural analytics is developed and implemented. Two datasets ‘People data’ and ‘Device data’ were linked and matched using social behaviours exhibited by individuals whose information are contained in the People data and by devices whose addresses show specific social behaviours of individuals who use the devices. A match score was generated to show the accuracy of a pair of records from the different datasets (i.e. to show if both records are indeed a match or not).en_US
dc.description.sponsorshipAUST and AfDB.en_US
dc.subjectOdedina Omolade Temitopeen_US
dc.subjectProf. Ekpe Okoraforen_US
dc.subject2019 Computer Science and Engineering Thesesen_US
dc.subjectMatch Scoreen_US
dc.subjectTelecommunication Industryen_US
dc.subjectSocial Behaviouren_US
dc.subjectProbabilistic Matching Algorithmsen_US
dc.titleEmploying Probabilistic Matching Algorithms for Identity Management in the Telecommunication Industryen_US

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  • Computer Science105

    This collection contains Computer Science Student's Theses from 2009-2022

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