Computing personalized probabilistic familiarity based on known artifact data

A computer program product comprising a computer readable storage medium having stored thereon:

• program instructions programmed to receive the identity of a first user;
• program instructions programmed to receive a first dataset pertaining to the first user;
• program instructions programmed to build an ontology of artifacts known to the first user, where the ontology includes a domain and a plurality of artifacts, the artifacts having corresponding characteristics, where at least one characteristic is shared between two or more artifacts;
• program instructions programmed to receive the identity of a first artifact, wherein the first artifact is not included in the ontology;
• program instructions programmed to apply 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
• program instructions programmed to report 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.

A computer system comprising:

• a processor(s) set;
• and
• a computer readable storage medium;
• wherein:
• the processor set is structured, located, connected and/or programmed to run program instructions stored on the computer readable storage medium;
• and
• the program instructions include:
• program instructions programmed to receive the identity of a first user;
• program instructions programmed to receive a first dataset pertaining to the first user;
• program instructions programmed to build an ontology of artifacts known to the first user, where the ontology includes a domain and a plurality of artifacts, the artifacts having corresponding characteristics, where at least one characteristic is shared between two or more artifacts;
• program instructions programmed to receive the identity of a first artifact, wherein the first artifact is not included in the ontology;
• program instructions programmed to apply 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
• program instructions programmed to report 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.