Methods and apparatus for predicting and selectively collecting preferences based on personality diagnosis
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United States of America Patent
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Dec 2, 2003
Grant Date -
N/A
app pub date -
Jul 31, 2000
filing date -
Jul 31, 2000
priority date (Note) -
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Abstract
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.
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