System and method for providing personalized recommendations

US9251527B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9251527-B2
Application numberUS-201213598124-A
CountryUS
Kind codeB2
Filing dateAug 29, 2012
Priority dateAug 29, 2011
Publication dateFeb 2, 2016
Grant dateFeb 2, 2016

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Abstract

Official abstract text for this publication.

A system and method for providing a personalized recommendation from a series of partial preferences is presented. A preference distribution of a population including a plurality of weighted ranked lists is identified. A revealed preference of a user is compared to the plurality of ranked lists. An affinity weight between the user and each of the plurality of ranked lists is assigned, and a weighted average of each of the affinity weights is taken.

First claim

Opening claim text (preview).

What is claimed is: 1. A method for inferring the preferences of a user in relation to a population with a computer comprising a processor and a memory containing non-transitory instructions configured to be executed by the processor, comprising the steps of: producing a sparse preference distribution of said population comprising a plurality of complete ranked lists and a weight of each of said plurality of ranked lists; comparing a revealed preference of said user to one of said plurality of ranked lists; assigning, based upon said comparing, an affinity weight between said user and each of said plurality of ranked lists; taking a weighted average of each of said affinity weights; and representing each of said plurality of ranked lists as a two dimensional partial comparison matrix of entries comprising a first index and a second index, wherein each index indicates an item and each entry of said matrix of entries is set to a first value if said first index item is preferred to said second index item, and otherwise set to a second value if said second index item is preferred to said first index item. 2. The method of claim 1 , wherein said affinity weight between said user and a ranked list is proportional to how similar said revealed preference of said user is to said ranked list. 3. The method of claim 1 , wherein said first value is one and said second value is zero. 4. The method of claim 1 , further comprising the steps of: receiving, by said computer, a plurality of partial preferences; learning said sparse preference distribution from said plurality of partial preferences; and processing said sparse distribution to rank a first preference list against a second preference list. 5. The method of claim 4 , further comprising the step of selecting said plurality of partial preferences from said first preference list and said second preference list. 6. A method for inferring the preferences of a user in relation to a population with a computer comprising a processor and a memory containing non-transitory instructions configured to be executed by the processor, comprising the steps of: identifying a sparse preference distribution of said population comprising a plurality of ranked lists and a weight of each of said plurality of ranked lists; comparing a revealed preference of said user to one of said plurality of ranked lists; assigning, based upon said comparing, an affinity weight between said user and each of said plurality of ranked lists; taking a weighted average of each of said affinity weights; and representing each of said plurality of ranked lists as a two dimensional partial comparison matrix of entries comprising a first index and a second index, wherein each index indicates an item and each entry of said matrix of entries is set to a first value if said first index item is preferred to said second index item, and otherwise set to a second value if said second index item is preferred to said first index item. 7. The method of claim 6 , wherein said first value is one and said second value is zero.

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Classifications

  • Market modelling; Market analysis; Collecting market data · CPC title

  • Market segmentation · CPC title

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What does patent US9251527B2 cover?
A system and method for providing a personalized recommendation from a series of partial preferences is presented. A preference distribution of a population including a plurality of weighted ranked lists is identified. A revealed preference of a user is compared to the plurality of ranked lists. An affinity weight between the user and each of the plurality of ranked lists is assigned, and a wei…
Who is the assignee on this patent?
Shah Devavrat, Farias Vivek Francis, Jagabathula Srikanth, and 2 more
What technology area does this patent fall under?
Primary CPC classification G06Q30/0201. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Feb 02 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).