Pangenetic web satisfaction prediction system
First Claim
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1. A computer based method for online prediction of user satisfaction with an item, comprising:
- a) receiving at least one item preference associated with a user;
b) accessing pangenetic data, said pangenetic data including both genetic and epigenetic data, associated with the user;
c) accessing a dataset containing one or more levels of satisfaction associated with the at least one item preference, wherein said pangenetic data are correlated with the one or more levels of satisfaction, wherein the correlations between the pangenetic data and the one or more levels of satisfaction contained in the dataset are previously determined based on statistical associations which indicate the strength of association between levels of satisfaction and wherein pangenetic data associated with a group of individuals and the pangenetic data correlated with the one or more levels of satisfaction are combinations of pangenetic data selected from pangenetic profiles associated with said group of individuals;
d) determining for each level of satisfaction, the quantity of matches between the pangenetic data correlated with that level of satisfaction and the pangenetic data associated with the user; and
e) computing a score for each level of satisfaction using a quantitative similarity measure that processes the quantity of matches, and selecting the level of satisfaction having the highest score as the level of satisfaction the user is predicted to experience and transmitting as output, based on the quantity of matches determined for each level of satisfaction, a level of satisfaction the user is predicted to experience with respect to the at least one item preference.
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Abstract
Computer based systems, methods, software and databases are presented in which correlations between web item preferences and pangenetic (genetic and epigenetic) attributes of individuals are used for pangenetic based web item satisfaction prediction in which a user can request and receive online predictions of their satisfaction with web items that are based on the user'"'"'s pangenetic makeup. Data masking can be used to maintain privacy of sensitive portions of the pangenetic data.
219 Citations
18 Claims
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1. A computer based method for online prediction of user satisfaction with an item, comprising:
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a) receiving at least one item preference associated with a user; b) accessing pangenetic data, said pangenetic data including both genetic and epigenetic data, associated with the user; c) accessing a dataset containing one or more levels of satisfaction associated with the at least one item preference, wherein said pangenetic data are correlated with the one or more levels of satisfaction, wherein the correlations between the pangenetic data and the one or more levels of satisfaction contained in the dataset are previously determined based on statistical associations which indicate the strength of association between levels of satisfaction and wherein pangenetic data associated with a group of individuals and the pangenetic data correlated with the one or more levels of satisfaction are combinations of pangenetic data selected from pangenetic profiles associated with said group of individuals; d) determining for each level of satisfaction, the quantity of matches between the pangenetic data correlated with that level of satisfaction and the pangenetic data associated with the user; and e) computing a score for each level of satisfaction using a quantitative similarity measure that processes the quantity of matches, and selecting the level of satisfaction having the highest score as the level of satisfaction the user is predicted to experience and transmitting as output, based on the quantity of matches determined for each level of satisfaction, a level of satisfaction the user is predicted to experience with respect to the at least one item preference. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A program storage device readable by a machine and containing a set of instructions which, when read by the machine, causes execution of a computer based method for online prediction of user satisfaction with an item, comprising:
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a) receiving at least one item preference associated with a user; b) accessing pangenetic data, said pangenetic data including both genetic and epigenetic data, associated with the user; c) accessing a dataset containing one or more levels of satisfaction associated with the at least one item preference, wherein pangenetic data are correlated with the one or more levels of satisfaction, wherein the correlations between the pangenetic data and the one or more levels of satisfaction contained in the dataset are previously determined based on statistical associations which indicate the strength of association between levels of satisfaction and pangenetic data associated with a group of individuals and wherein the pangenetic data correlated with the one or more levels of satisfaction are combinations of pangenetic data selected from pangenetic profiles associated with said group of individuals; d) determining for each level of satisfaction, the quantity of matches between the pangenetic data correlated with that level of satisfaction and the pangenetic data associated with the user; and e) computing a score for each level of satisfaction using a quantitative similarity measure that processes the quantity of matches, and selecting the level of satisfaction having the highest score as the level of satisfaction the user is predicted to experience and transmitting as output, based on the quantity of matches determined for each level of satisfaction, a level of satisfaction the user is predicted to experience with respect to the at least one item preference. - View Dependent Claims (16)
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17. A computer database system for online prediction of user satisfaction with an item, comprising:
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a) a memory containing;
i) a first data structure containing pangenetic data, said pangenetic data including both genetic and epigenetic data, associated with the user;
ii) a second data structure containing one or more levels of satisfaction associated with at least one item preference associated with the user, wherein pangenetic data are correlated with the one or more levels of satisfaction, wherein the correlations between the pangenetic data and the one or more levels of satisfaction contained in the dataset are previously determined based on statistical associations which indicate the strength of association between levels of satisfaction and pangenetic data associated with a group of individuals and wherein the pangenetic data correlated with the one or more levels of satisfaction are combinations of pangenetic data selected from pangenetic profiles associated with said group of individuals;b) a processor for;
i) receiving the at least one item preference associated with the user;
ii) accessing the first data structure;
iii) accessing the second data structure;
iv) determining for each level of satisfaction, the quantity of matches between the pangenetic data correlated with that level of satisfaction and the pangenetic data associated with the user; and
v) computing a score for each level of satisfaction using a quantitative similarity measure that processes the quantity of matches, and selecting the level of satisfaction having the highest score as the level of satisfaction the user is predicted to experience and transmitting as output, based on the quantity of matches determined for each level of satisfaction, a level of satisfaction the user is predicted to experience with respect to the at least one item preference. - View Dependent Claims (18)
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Specification