Patent Document ID: 9852380
Application ID: 14587021
Patent Flag: 1

Claim One:
1. A computer-implemented method comprising: receiving the identity of a first user; receiving a first dataset pertaining to the first user; building, utilizing the first dataset, an ontology of artifacts known to the first user, where the ontology includes a domain of food and a plurality of artifacts that include food recipes, the artifacts having corresponding characteristics that include food ingredients, and where at least one characteristic is shared between two or more artifacts; receiving the identity of a first artifact, wherein the first artifact is not included in the ontology; applying a probabilistic familiarity algorithm to the ontology with respect to the first artifact to yield a probabilistic familiarity value for the first artifact with respect to the first user; and reporting the probabilistic familiarity value to the first user; wherein: the first dataset is received over a computer network; the first dataset includes at least one piece of personalized information for the first user; and applying the probabilistic familiarity algorithm to the ontology with respect to the first artifact to yield a probabilistic familiarity value for the first artifact with respect to the first user includes: calculating a prior probability distribution for each artifact of the ontology using the probabilistic familiarity algorithm, wherein calculating the prior probability distribution for a given artifact using the probabilistic familiarity algorithm includes: determining an ontology closeness representing an amount of closeness between the given artifact and a set of artifacts that are determined to be similar to the given artifact based on the artifacts' respective characteristics, determining a social proximity measure representing an amount of closeness between the first user and a set of persons within a social network of the first user, determining a temporal proximity measure representing an amount of closeness between a time the given artifact was observed by the first user and a set of time points prior to the time the given artifact was observed by the first user, and utilizing the ontology closeness, the social proximity measure, and the temporal proximity measure to create a weighted frequency for the given artifact, the weighted frequency corresponding to the prior probability distribution; and calculating a probabilistic familiarity value for the first artifact by adding the first artifact to the set of artifacts and calculating the first artifact's prior probability distribution using the probabilistic familiarity algorithm.