The Power of Recommender

"Much as steam engines energised the Industrial Age, recommendation engines are the prime movers digitally driving 21st-century advice worldwide"

Recommender systems are the prime technology for improving business in the digital world. The list is endless, from movie recommendations on Netflix to video recommendations on YouTube, to playlist recommendations on Spotify, to best route recommendations in Google Maps.

Recommender systems are a subset of Artificial Tools designed to learn user preferences from the vast amount of data, including but not limited to user-item interactions, past user behaviours, and so on. They are capable of delivering individualised, tailor-made recommendations that enhance user experience while boosting business revenue.

In SEDIMARK our goal is not only to provide a secure data-sharing platform, but also to enhance the experience of our users through the use of Recommender Systems at multiple levels:

• Navigating the vast amount of datasets available within the platform
• Suggesting ready-made AI models relevant to the given dataset
• Suggesting computational services capable of handling the given dataset

Recommending Datasets:

SEDIMARK is a platform offering a vast amounts of data available for purchase in a secure way. To enhance the user experience, the team at UCD is developing cutting-edge recommender systems specifically targeted at dataset recommendation. The system will leverage data from past users’ behaviour such as past purchases, past browsing history, or behaviour of other similar users.

Recommending Ready-made AI Models:

Apart from datasets, SEDIMARK will also offer ready-made AI models capable of extracting information from the specific dataset, such as for example weather forecast AI model that can learn from weather data collected by sensors. The recommender system in this category will be able to suggest the most relevant AI models for the given dataset. This will allow the users to fully explore the potential of the purchased dataset within the SEDIMARK platform.

Recommending Computational Services:

Depending on the size of the purchased dataset and the complexity of the AI model, SEDIMARK will also aim to suggest the appropriate computation services that can carry out the learning process and are available within the SEDIMARK platfrom. 

Using a single platform, users in SEDIMARK will be able to perform data discovery, learn insights from a given dataset using AI models and utilise computational services.