System and method for determining multi-party communication engagement
US-2024428274-A1 · Dec 26, 2024 · US
US9251527B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9251527-B2 |
| Application number | US-201213598124-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 29, 2012 |
| Priority date | Aug 29, 2011 |
| Publication date | Feb 2, 2016 |
| Grant date | Feb 2, 2016 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
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.
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.
Market modelling; Market analysis; Collecting market data · CPC title
Market segmentation · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.