Method and System for Predicting Personal Preferences
First Claim
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1. A method of developing a model predictive of preferences of people among decision objects having one or more attributes, the method comprising the steps of:
- a. obtaining a data set indicative of characteristics and expressed affinity for attributes of the decision objects pertaining to a plurality of people;
b. obtaining sets of predictive models based at least in part on the data set, wherein a first set comprises predictive models based on segmenting the data set by said demographic characteristics and a second set comprises predictive models based on segmenting the data set by said affinity for the attributes;
c. selecting a predictive model from each of the first and second sets for a person based on the person'"'"'s characteristics and the person'"'"'s expressed affinity for the attributes of the decision objects;
d. calculating the person'"'"'s predicted affinity for the attributes of the decision objects using each of the selected models;
e. calculating a weighting factor for each of the selected models; and
f. combining the calculated predicted affinities for the attributes of the decision objects based on the weighting factors to produce a predictive model for the person'"'"'s affinity for the attributes of the decision objects.
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Abstract
The invention provides techniques for building multiple predictive models of individuals'"'"' affinities for attributes of objects and/or services. The accuracies of multiple predictive models are measured and the models are combined based on the measurements, resulting in a more accurate predictive model of individual-specific affinities for attributes of the objects and/or services.
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Citations
30 Claims
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1. A method of developing a model predictive of preferences of people among decision objects having one or more attributes, the method comprising the steps of:
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a. obtaining a data set indicative of characteristics and expressed affinity for attributes of the decision objects pertaining to a plurality of people; b. obtaining sets of predictive models based at least in part on the data set, wherein a first set comprises predictive models based on segmenting the data set by said demographic characteristics and a second set comprises predictive models based on segmenting the data set by said affinity for the attributes; c. selecting a predictive model from each of the first and second sets for a person based on the person'"'"'s characteristics and the person'"'"'s expressed affinity for the attributes of the decision objects; d. calculating the person'"'"'s predicted affinity for the attributes of the decision objects using each of the selected models; e. calculating a weighting factor for each of the selected models; and f. combining the calculated predicted affinities for the attributes of the decision objects based on the weighting factors to produce a predictive model for the person'"'"'s affinity for the attributes of the decision objects. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. An article of manufacture having computer-readable program portions embodied thereon for developing a model predictive of preferences of people among decision objects having a plurality of attributes, the article comprising computer-readable instructions for:
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a. obtaining a data set indicative of characteristics and expressed affinity for attributes of the decision objects pertaining to a plurality of people; b. obtaining sets of predictive models based at least in part on the data set, wherein a first set comprises predictive models based on segmenting the data set by said demographic characteristics and a second set comprises predictive models based on segmenting the data set by said affinity for the attributes; c. selecting a predictive model from each of the first and second sets for a person based on the person'"'"'s demographic characteristics and the person'"'"'s expressed affinity for the attributes of the decision objects; d. calculating the person'"'"'s predicted affinity for the attributes of the decision objects using each of the selected models; e. calculating a weighting factor for each of the selected models; and f. combining the calculated predicted affinities for the attributes of the decision objects based on the weighting factors to produce a predictive model for the person'"'"'s affinity for the attributes of the decision objects. - View Dependent Claims (22, 23, 24, 25)
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26. A system for developing a model predictive of preferences of people among decision objects having a plurality of attributes, the system comprising
a modeling engine configured to: -
i) apply sets of predictive models to a data set indicative of characteristics and expressed affinity for attributes of a plurality of decision objects pertaining to a plurality of people, wherein a first set of predictive models comprises predictive models segmented by the characteristics and a second set of predictive models comprises predictive models segmented by the affinity for the attributes of the decision objects; ii) select a predictive model from each of the first and second sets for a person based on the person'"'"'s characteristics and the person'"'"'s expressed affinity for the attributes of the decision objects; iii) calculate the person'"'"'s predicted affinity for the attributes of the plurality of decision objects using each of the selected models; iv) calculate a weighting factor for each of the selected models; and v) combine the calculated predicted affinities for each attribute of the decision objects based on the weighting factors to produce a predictive model for the individual'"'"'s affinity for the attributes of the decision objects. - View Dependent Claims (27, 28, 29, 30)
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Specification