Determining Utility Functions from Ordinal Rankings
First Claim
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1. A method of providing goods or services, said method comprising:
- requesting a list of goods or services available from a supplier for purchase by a buyer through a computer system;
associating attributes with said goods or services, wherein said attributes correspond to characteristics of said goods or services and are measured according to a quantifiable standard;
providing a subset list of said goods or services as a training example to a multi-layered neural network;
automatically generating a utility function comprising weighted components associated with said attributes based on training performed by the neural network;
automatically ranking all said goods or services according to said utility function;
presenting to said buyer a ranked list comprising a pair of the highest ranked goods or services as a representative sample from all said goods or services available from said supplier;
evaluating said ranked list to determine whether said highest ranked goods or services match a buyer preference corresponding to said attributes of said goods or services;
submitting the evaluation to said neural network;
inputting said evaluation into said utility function;
re-ranking all said goods or services according to said attributes and said evaluation;
presenting to said buyer a re-ranked list comprising a pair of the highest re-ranked goods or services as a representative sample from all said goods or services available from said supplier;
re-evaluating said re-ranked list to determine whether said highest re-ranked goods or services match said buyer preference corresponding to said attributes of said goods or services;
iteratively repeating the submitting process through the re-evaluating process until said re-ranked list matches said ranked list; and
presenting to said buyer a final ranked list of all said goods or services ranked according to buyer preferences corresponding to said attributes.
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Abstract
A user'"'"'s preference structure in respect of alternative “objects” with which the user is presented is captured in a multi-attribute utility function. The user ranks these competing objects in order of the user'"'"'s relative preference for such objects. A utility function that defines the user'"'"'s preference structure is provided as output on the basis of this relative ranking. This technique can be used to assist a buyer in selecting between multi-attribute quotes or bids submitted by prospective suppliers to the buyer.
10 Citations
20 Claims
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1. A method of providing goods or services, said method comprising:
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requesting a list of goods or services available from a supplier for purchase by a buyer through a computer system;
associating attributes with said goods or services, wherein said attributes correspond to characteristics of said goods or services and are measured according to a quantifiable standard;
providing a subset list of said goods or services as a training example to a multi-layered neural network;
automatically generating a utility function comprising weighted components associated with said attributes based on training performed by the neural network;
automatically ranking all said goods or services according to said utility function;
presenting to said buyer a ranked list comprising a pair of the highest ranked goods or services as a representative sample from all said goods or services available from said supplier;
evaluating said ranked list to determine whether said highest ranked goods or services match a buyer preference corresponding to said attributes of said goods or services;
submitting the evaluation to said neural network;
inputting said evaluation into said utility function;
re-ranking all said goods or services according to said attributes and said evaluation;
presenting to said buyer a re-ranked list comprising a pair of the highest re-ranked goods or services as a representative sample from all said goods or services available from said supplier;
re-evaluating said re-ranked list to determine whether said highest re-ranked goods or services match said buyer preference corresponding to said attributes of said goods or services;
iteratively repeating the submitting process through the re-evaluating process until said re-ranked list matches said ranked list; and
presenting to said buyer a final ranked list of all said goods or services ranked according to buyer preferences corresponding to said attributes. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A program storage device readable by computer, tangibly embodying a program of instructions executable by said computer to perform a method of providing goods or services, said method comprising:
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requesting a list of goods or services available from a supplier for purchase by a buyer through a computer system;
associating attributes with said goods or services, wherein said attributes correspond to characteristics of said goods or services and are measured according to a quantifiable standard;
providing a subset list of said goods or services as a training example to a multi-layered neural network;
automatically generating a utility function comprising weighted components associated with said attributes based on training performed by the neural network;
automatically ranking all said goods or services according to said utility function;
presenting to said buyer a ranked list comprising a pair of the highest ranked goods or services as a representative sample from all said goods or services available from said supplier;
evaluating said ranked list to determine whether said highest ranked goods or services match a buyer preference corresponding to said attributes of said goods or services;
submitting the evaluation to said neural network;
inputting said evaluation into said utility function;
re-ranking all said goods or services according to said attributes and said evaluation;
presenting to said buyer a re-ranked list comprising a pair of the highest re-ranked goods or services as a representative sample from all said goods or services available from said supplier;
re-evaluating said re-ranked list to determine whether said highest re-ranked goods or services match said buyer preference corresponding to said attributes of said goods or services;
iteratively repeating the submitting process through the re-evaluating process until said re-ranked list matches said ranked list; and
presenting to said buyer a final ranked list of all said goods or services ranked according to buyer preferences corresponding to said attributes. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification