The user semantic fingerprint is at the heart of Rumo’s recommendation system. It’s what allows the visualization of users’ history and preferences.
In Rumo’s dashboard, the user semantic fingerprint is illustrated in the section “recommendation preview”, “user recommendation” and then “profile”. They are bubbles with each of them having a specific weight based on the user’s interaction with each content on the platform. They are divided into different categories: “tags”, “moods”, “character”, “format”, … You know what they say: “A picture is worth a thousand words”, and we agree! Having simple but meaningful visualizations is much better than dozen of pages of data about end users. Note that not only can you see it, but you also have the option to let users have access to this section of their profile by integrating the User Profile endpoint.
Find the category combinations that work best by looking at different profiles to see what interests your users. You can get an overview of the top ten keywords in a user profile and even zoom in on each category to discover a user’s favorite actor or filmmaker.
What’s next ?
The next step would be to let users modify these keywords and weights themselves. This way, it empowers them and make them actors of their own recommendation process. By doing so, they would be able to test new keyword combinations and thus increase serendipity by themselves.
It’s already on this year’s roadmap, but don’t hesitate to check out our public roadmap and vote for this feature to let us know how important it is to you.