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AssigneeMicrosoft Corporation
InventorsEric J. Horvitz, David M. Pennock
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A new recommendation technique, referred to as “personality diagnosis”, can be seen as a hybrid between memory-based and model-based collaborative filtering techniques. Using personality diagnosis, all data can be maintained throughout the processes, new data can be added incrementally, and predictions have meaningful probabilistic semantics. Each entity's reported attributes can be interpreted as a manifestation of their underlying personality type. Personality type can be encoded simply as a vector of the entity's “true” values for attributes in the database. Given an active entity's known attribute values, the probability that they have the same personality type as every other entity can be determined. Then, the probability that they will have a given value for a valueless attribute can then be determined based on the entity's personality type. The probabilistic determinations can be used to determine expected value of information.
A method for using a machine to predict a value of an attribute, having no assigned value, of an active entity, the method comprising:
A method for using a machine to generate, for each of a number of personality types defined by a plurality of other entities, probabilities that an active entity is that personality type, the method comprising:
A method for using a machine to determine, for each possible value of an attribute having no assigned value, a probability that an active entity values the attribute with the current possible value, the method comprising:
An apparatus for predicting the value of an attribute of an active entity, the apparatus comprising:
Dependencies are inferred from the claim text.