| CPC G09B 5/065 (2013.01) [G06F 3/165 (2013.01); G09B 5/00 (2013.01); G09B 7/00 (2013.01); G09B 7/02 (2013.01); G11B 27/19 (2013.01); G11B 27/34 (2013.01)] | 18 Claims |

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1. A computer-implemented method of recommending content items, the method comprising:
determining, via a processor, at least one user characteristic of a user based on user engagement with at least a first content item stored in a knowledge base, wherein the first content item is stored in the knowledge base according to a linking structure based on a first concept associated with the first content item, and wherein the knowledge base and first content item are stored in one or more memory components accessible by the processor;
generating, via the processor, a user model configured to predict a knowledge level of the user, wherein the user model comprises a set of nodes based on the at least one user characteristic, and wherein the user model comprises a factor graph that includes the set of nodes;
applying, via the processor, the user model to predict the knowledge level;
generating, via the processor, a recommendation of at least a portion of a second content item based, at least in part, on the predicted knowledge level, wherein the at least a portion of the second content item is stored in the knowledge base according to a linking structure based on a second concept associated with the at least a portion of the second content item, and wherein the second content item is stored in the one or more memory components accessible by the processor; and
displaying, via the processor, the at least a portion of the second content item via a graphical user interface.
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