Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.682993
Title: A framework for adaptive personalised e-advertisements
Author: Al Qudah, Dana
ISNI:       0000 0004 5916 1255
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2016
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Abstract:
The art of personalised e-advertising relies on attracting the user‟s attention to the recommended product, as it relates to their taste, interest and data. Whilst in practice, companies attempt various forms of personalisation; research of personalised e-advertising is rare, and seldom routed on solid theory. Adaptive hypermedia (AH) techniques have contributed to the development of personalised tools for adaptive content delivery, mostly in the educational domain. This study explores the use of these theories and techniques in a specific field – adaptive e-advertisements. This is accomplished firstly by structuring a theoretical framework that roots adaptive hypermedia into the domain of e-advertising and then uses this theoretical framework as the base for implementing and evaluating an adaptive e-advertisement system called “MyAds”. The novelty of this approach relies on a systematic design and evaluation based on adaptive hypermedia taxonomy. In particular, this thesis uses a user centric methodology to design and evaluate the proposed approach. It also reports on evaluations that investigated users‟ opinions on the appropriate design of MyAds. Another set of evaluations reported on users‟ perceptions of the implemented system, allowing for a reflection on the users‟ acceptance level of e-advertising. The results from both implicit and explicit feedback indicated that users found the MyAds system acceptable and agreed that the implemented user modelling and AH features within the system contributed to achieving acceptance, within their e-advertisement experience due to the different personalisation methods.
Supervisor: Not available Sponsor: University of Jordon
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.682993  DOI: Not available
Keywords: QA76 Electronic computers. Computer science. Computer software
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