Recommendation engine that processes data including user data to provide recommendations and explanations for the recommendations to a user

A server computer comprising a processor and a non-transitory computer readable medium, the non-transitory computer readable medium comprising code executable by the processor to implement a computer-implemented method for generating explanatory data from a personalized recommendations process for a primary user based at least on stored data about the primary user, the method comprising:

• determining the primary user for whom explanatory data is to be generated, the primary user being one of a plurality of users over which recommendations are considered;
• obtaining, at a server computer, data related to a set of relevant users, wherein the set of relevant users comprises one or more users in the plurality of users that are deemed relevant to the primary user, wherein relevancy of a user in the set of relevant users to the primary user is based, at least on part, on similarities, according to stored user data, between the relevant user and the primary user;
• obtaining, at the server computer, entity data from a plurality of data sources, wherein the entity data is associated with an entity in a plurality of entities;
• storing the entity data at the server computer, wherein the entity data associated with the plurality of entities is stored in an entity database;
• determining, at the server computer, one or more entities relevant to the primary user based on the data related to the one or more entities;
• determining, by the server computer, one or more potential candidate factors based on at least the one or more relevant entities;
• and
• generating, by the server computer, explanation data based on the one or more potential candidate factors used in the personalized recommendations process.