This paper assesses both content-based and collaborative recommendation algorithms. Using a combination of different metrics, it discusses their relative advantages and disadvantages as well as the viability of both models from a business perspective.

The potential future applications of chatbots are astounding, in fields as varied as education and retail. This paper considers the ways chatbots are already being used in a wide range industries, and looks forward to the future.

This paper focuses on bettering the current design of E-bikes with an intent to improve the user-centred approach. It does this by considering an existing company case study, compiling an HTA of the process, and identifying problems. For each of the issues noted, it then offers a suggestion to improve public E-bikes as a whole.

This paper aims to present a newly improved design of E-Scooters and their system by establishing a framework for a user-centered design process. Hierarchical task analysis, as well as knowledge of the general socio-technical system, is then applied to identify areas of improvement within the system, and using this as a reference, user requirements are stated and justified, and a low-fidelity prototype of the electric scooter is constructed.

This paper aims to investigate how AI works within the context of video content recommendations and will specifically focus on how streaming services like Netflix, Sky, and Amazon Prime Video decide which content to present to their subscribers to choose from. This paper will also explore some of the limitations of content recommendations and how future developments aim to overcome them.