Rummble labs have developed a unique trust algorithm using a combination of user and item based filtering in combination with mapping tags to create an engine that calculates trust scores between people and provides personalised recommendations for content.
Through tracing user activity such as purchases, reviews, ratings, listens, check ins, likes, we are able to gain a complete understanding and return accurate and relevant recommendations.
We recognise that people inherently trust the opinions of those they know. We link the actions of those the user follows or is connected to, to give added credibility to the recommendations. This translates to paths of trust which can precisely link people of similar tastes and opinions. In addition we map those people who they are not connected to but return a high level of trust through indirect interaction.
Rummble Labs API
Rummble Labs provide an adaptable API which is highly scalable to process large volumes of data. It has been developed over 3 years in conjunction with the research department at QUT.
Our scientific API uses a combination of methodologies across multiple verticals to return the most accurate and relevant material for each individual.The API is constantly evolving in real time based on most recent behaviours
Our intelligent engine picks the best combination of indicators to apply in each context. It processes millions of data points and is growing with each validation we trial.
