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E-commerce website personalisation based on ontological profiling

Edwards, Natalia 2015. E-commerce website personalisation based on ontological profiling. PhD Thesis, Cardiff University.
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Electronic commerce has become an important part of our consumer lives, and we increasingly choose to do more and more of our shopping online. Along with the growth of online sales, the number of e-commerce retailers has also increased. This has inevitably put additional demands on existing companies as well as new market entrants to ensure that their growth (if not just survival) as well as competitiveness are sustainable and evolving. Web personalisation has been adopted as a means to support business sustainability and competitiveness. It is now increasingly common and has been recognised by e-commerce businesses and consumers as a feature and functionality, expected to be offered as ‘standard’. Recent World Wide Web technology advances have greatly improved the way ecommerce websites are designed and deployed. However, the analysis of academic literature and professional practices shows that these advances are not used to their full potential. This research gap is an opportunity for this community to consider how techniques such as ontologies could be used to enhance personalisation of e-commerce websites. This thesis presents a novel approach to e-commerce website personalisation (PERSONTO), and in particular, personalisation of content presentation. Personalisation is achieved by means of an ontology-based e-shopper profiling. For this purpose, a reusable, extendible and Semantic Web compatible customer profiling ontology OntoProfi is designed and implemented. A ‘proof-of-concept’ prototype of PERSONTO confirmed the feasibility of the proposed approach. The analysis of achievements of the research objectives and outcomes showed that the approach is flexible, extendible and reusable, and that it was achieved by using systematic methods in the system design and implementation of the prototype. The evaluation of the acceptance of the proposed approach suggests there is a high level of acceptance of the approach by the prospective end users and e-commerce developers.

Item Type: Thesis (PhD)
Date Type: Completion
Status: Unpublished
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: e-commerce personalisation, web personalisation, ontological customer profiling
Date of First Compliant Deposit: 24 June 2016
Last Modified: 13 Jun 2022 16:08

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