ABSTRACT
The 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).
Temitope, O (2021). Employing Probabilistic Matching Algorithms For Identity Management In The Telecommunication Industry. Afribary. Retrieved from https://afribary.com/works/employing-probabilistic-matching-algorithms-for-identity-management-in-the-telecommunication-industry
Temitope, Odedina "Employing Probabilistic Matching Algorithms For Identity Management In The Telecommunication Industry" Afribary. Afribary, 15 Apr. 2021, https://afribary.com/works/employing-probabilistic-matching-algorithms-for-identity-management-in-the-telecommunication-industry. Accessed 16 Nov. 2024.
Temitope, Odedina . "Employing Probabilistic Matching Algorithms For Identity Management In The Telecommunication Industry". Afribary, Afribary, 15 Apr. 2021. Web. 16 Nov. 2024. < https://afribary.com/works/employing-probabilistic-matching-algorithms-for-identity-management-in-the-telecommunication-industry >.
Temitope, Odedina . "Employing Probabilistic Matching Algorithms For Identity Management In The Telecommunication Industry" Afribary (2021). Accessed November 16, 2024. https://afribary.com/works/employing-probabilistic-matching-algorithms-for-identity-management-in-the-telecommunication-industry