COMPUTING PERSONALIZED PROBABILISTIC FAMILIARITY BASED ON KNOWN ARTIFACT DATA

Software that uses personalized information pertaining to a user to determine how familiar (or “novel” or “surprising”) a new artifact will be to the user, by performing the following steps: (i) receiving the identity of a first user; (ii) receiving a first dataset pertaining to the first user; (iii) receiving the identity of a first artifact; and (iv) applying a probabilistic familiarity algorithm to the first dataset with respect to the first artifact to yield a probabilistic familiarity value for the first artifact with respect to the first user. The first dataset is received over a computer network, and the first dataset includes at least one piece of personalized information for the first user.