Method and system for robust social choices and vote elicitation
AssigneeGoogle Inc.
InventorsTian Lu, Craig Edgar Boutilier
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Abstract
The present invention is a method and system for learning models of the preferences of members drawn from some population or group, utilizing arbitrary paired preferences of those members, in any commonly used ranking model. In particular the present invention involves techniques for learning Mallows models, and mixtures thereof, from pairwise preference data.
Claims17
A computer implemented method of identifying and ranking preferences regarding a plurality of options, for a group including two or more members, the method comprising:
- (a) obtaining from one or more data sources, preference information, including partial preference information, for the members, or a subset of the members, wherein the partial preference information may include a set of pairwise comparisons involving one or more of the options;
- (b) analyzing, by operation of one or more server computers, the pairwise comparisons so as to learn one or more statistical models for inferring and ranking a set of preferences based on the partial preference information;
- and
- (c) applying the one or more statistical models so as to identify the set of preferences and rank the options.
A computer network implemented system for identifying and ranking preferences regarding a plurality of options, for a group including two or more members, the system comprising:
- (a) one or more server computers, connected to an interconnected network of computers, and linked to a server application;
- (b) the server application includes or is linked to an preference inference engine that:
- (i) obtains from one or more data sources linked to the one or more server computers, preference information, including partial preference information, for the members, or a subset of the members, wherein the partial preference information may include a set of pairwise comparisons involving one or more of the options;
- (ii) analyzing the pairwise comparisons so as to learn one or more statistical models for inferring and ranking a set of preferences based on the partial preference information;
- and
- (iii) applying the one or more statistical models so as to identify the preferences and rank the set of options.
Dependencies are inferred from the claim text.