Explanation of people's recommendations
💡 "In general, we don’t blindly trust those who can’t explain their reasoning." - IBM
One of the key reasons attendees go to an event is to network. However, it can be daunting to find the right people to talk to or kick-start conversations with strangers. Swapcard’s AI-powered networking makes meeting and talking with other event attendees a piece of cake.
Our AI recommends matches based on profile similarities. With this new feature, attendees can see why they were matched with a particular person! This helps them break the ice and provides them with topics of conversation.
For personalized people recommendations, the first level of explanations is displayed. It provides the attendee with general information on what people have in common.
Then, after clicking on the user profile, high-level explanations will be displayed with details. Attendees will find the events they have in common, interests, jobs, and so on.
How does it work?
The recommendations are based on your data, this includes your profile and the interactions that you have using the app. With this data, we create a Machine Learning model that highlights the links between your data and other data. This technique creates recommendations. A large graph is then created that links all the available data between each user according to similarities or associations found by the algorithm. These similarities or associations are the explanations.