Dynamic augmenting of relevance rankings using data from external ratings sources

Abstract

In general, embodiments of the present invention provide systems, methods and computer readable media for dynamically augmenting relevance rankings using data from external ratings sources.

1 - 11 . (canceled) 
     
     
         12 . An apparatus, comprising one or more processors and one or more storage devices storing instructions that are operable, when executed by the one or more processors, to cause the one or more processors to:
 receive an ordered list of trilateral inventory objects of a plurality of trilateral inventory objects, wherein each trilateral inventory object of the ordered list of trilateral inventory objects is associated with a respective relevance score, wherein the ordered list of trilateral inventory objects is ordered based at least in part on the relevance scores, and wherein each trilateral inventory object of the ordered list of trilateral inventory objects is described by a set of trilateral inventory object attributes that change on a real-time basis, including at least a trilateral inventory object category and ratings from an external ratings source;   for each trilateral inventory object of the ordered list of trilateral inventory objects:
 calculate an average category conversion rate using the respective conversion rates associated with each of the trilateral inventory objects associated with the trilateral inventory object category; 
 segment a rating range associated with the external ratings source into a set of subranges; 
 for each subrange of the set of subranges, calculate an average subrange conversion rate for the trilateral inventory objects having one or more ratings within the subrange; 
 calculate a boost scaling factor for the subrange based at least in part the average subrange conversion rate for the subrange, the average category conversion rate for the trilateral inventory object category, and a correlation coefficient for trilateral inventory objects within the trilateral inventory object category; and 
 calculate an updated relevance score based at least in part on the boost scaling factor; 
   reorder the ordered list of trilateral inventory objects based at least in part on the updated relevance scores to provide dynamically augmented relevance rankings for the plurality of trilateral inventory objects described by the set of trilateral inventory object attributes that change on a real-time basis; and   transmit, to a consumer device, real-time data associated with the dynamically augmented relevance rankings for the plurality of trilateral inventory objects to provide a real-time rendering of the dynamically augmented relevance rankings for the plurality of trilateral inventory objects via an electronic interface of the consumer device.   
     
     
         13 . The apparatus of  claim 12 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:
 configure a size of respective subranges from the set of subranges.   
     
     
         14 . The apparatus of  claim 12 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:
 configure a size of the set of subranges based at least in part on a number of trilateral inventory objects respectively included in subranges from the set of subranges.   
     
     
         15 . The apparatus of  claim 12 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:
 calculate the boost scaling factor for the subrange based at least in part on historical performance data associated with the plurality of trilateral inventory objects.   
     
     
         16 . The apparatus of  claim 12 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:
 calculate the boost scaling factor for the subrange based at least in part on cumulative distribution function data associated each subrange of the set of subranges.   
     
     
         17 . The apparatus of  claim 12 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:
 calculate the boost scaling factor in response to a determination that an amount of impression data collected from the trilateral inventory objects satisfies a predetermined threshold value.   
     
     
         18 . The apparatus of  claim 12 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:
 receive a user acceptance indication provided via user input to the electronic interface within a given time period that begins at the real-time rendering of the of the dynamically augmented relevance rankings for the plurality of trilateral inventory objects via the electronic interface.   
     
     
         19 . The apparatus of  claim 18 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:
 initiate redemption of a good, service or experience associated with at least one trilateral inventory object from the dynamically augmented relevance rankings for the plurality of trilateral inventory objects.   
     
     
         20 . A computer-implemented method, comprising:
 receiving, by a computing device comprising a processor, an ordered list of trilateral inventory objects of a plurality of trilateral inventory objects, wherein each trilateral inventory object of the ordered list of trilateral inventory objects is associated with a respective relevance score, wherein the ordered list of trilateral inventory objects is ordered based at least in part on the relevance scores, and wherein each trilateral inventory object of the ordered list of trilateral inventory objects is described by a set of trilateral inventory object attributes that change on a real-time basis, including at least a trilateral inventory object category and ratings from an external ratings source;   for each trilateral inventory object of the ordered list of trilateral inventory objects:
 calculating, by the computing device, an average category conversion rate using the respective conversion rates associated with each of the trilateral inventory objects associated with the trilateral inventory object category; 
 segmenting, by the computing device, a rating range associated with the external ratings source into a set of subranges; 
 for each subrange of the set of subranges, calculating, by the computing device, an average subrange conversion rate for the trilateral inventory objects having one or more ratings within the subrange; 
 calculating, by the computing device, a boost scaling factor for the subrange based at least in part the average subrange conversion rate for the subrange, the average category conversion rate for the trilateral inventory object category, and a correlation coefficient for trilateral inventory objects within the trilateral inventory object category; and 
 calculating, by the computing device, an updated relevance score based at least in part on the boost scaling factor; 
   reordering, by the computing device, the ordered list of trilateral inventory objects based at least in part on the updated relevance scores to provide dynamically augmented relevance rankings for the plurality of trilateral inventory objects described by the set of trilateral inventory object attributes that change on a real-time basis; and   transmitting, by the computing device and to a consumer device, real-time data associated with the dynamically augmented relevance rankings for the plurality of trilateral inventory objects to provide a real-time rendering of the dynamically augmented relevance rankings for the plurality of trilateral inventory objects via an electronic interface of the consumer device.   
     
     
         21 . The computer-implemented method of  claim 20 , further comprising:
 configuring, by the computing device, a size of respective subranges from the set of subranges.   
     
     
         22 . The computer-implemented method of  claim 20 , further comprising:
 configuring, by the computing device, a size of the set of subranges based at least in part on a number of trilateral inventory objects respectively included in subranges from the set of subranges.   
     
     
         23 . The computer-implemented method of  claim 20 , wherein the calculating the boost scaling factor for the subrange comprises calculating the boost scaling factor for the subrange based at least in part on historical performance data associated with the plurality of trilateral inventory objects. 
     
     
         24 . The computer-implemented method of  claim 20 , wherein the calculating the boost scaling factor for the subrange comprises calculating the boost scaling factor for the subrange based at least in part on cumulative distribution function data associated each subrange of the set of subranges. 
     
     
         25 . The computer-implemented method of  claim 20 , wherein the calculating the boost scaling factor for the subrange comprises calculating the boost scaling factor in response to a determination that an amount of impression data collected from the trilateral inventory objects satisfies a predetermined threshold value. 
     
     
         26 . The computer-implemented method of  claim 20 , further comprising:
 receiving, by the computing device, a user acceptance indication provided via user input to the electronic interface within a given time period that begins at the real-time rendering of the of the dynamically augmented relevance rankings for the plurality of trilateral inventory objects via the electronic interface.   
     
     
         27 . The computer-implemented method of  claim 20 , further comprising:
 initiating, by the computing device, redemption of a good, service or experience associated with at least one trilateral inventory object from the dynamically augmented relevance rankings for the plurality of trilateral inventory objects.   
     
     
         28 . A computer program product, stored on a computer readable medium, comprising instructions that when executed by one or more computers cause the one or more computers to:
 receive an ordered list of trilateral inventory objects of a plurality of trilateral inventory objects, wherein each trilateral inventory object of the ordered list of trilateral inventory objects is associated with a respective relevance score, wherein the ordered list of trilateral inventory objects is ordered based at least in part on the relevance scores, and wherein each trilateral inventory object of the ordered list of trilateral inventory objects is described by a set of trilateral inventory object attributes that change on a real-time basis, including at least a trilateral inventory object category and ratings from an external ratings source;   for each trilateral inventory object of the ordered list of trilateral inventory objects:
 calculate an average category conversion rate using the respective conversion rates associated with each of the trilateral inventory objects associated with the trilateral inventory object category; 
 segment a rating range associated with the external ratings source into a set of subranges; 
 for each subrange of the set of subranges, calculate an average subrange conversion rate for the trilateral inventory objects having one or more ratings within the subrange; 
 calculate a boost scaling factor for the subrange based at least in part the average subrange conversion rate for the subrange, the average category conversion rate for the trilateral inventory object category, and a correlation coefficient for trilateral inventory objects within the trilateral inventory object category; and 
 calculate an updated relevance score based at least in part on the boost scaling factor; 
   reorder the ordered list of trilateral inventory objects based at least in part on the updated relevance scores to provide dynamically augmented relevance rankings for the plurality of trilateral inventory objects described by the set of trilateral inventory object attributes that change on a real-time basis; and   transmit, to a consumer device, real-time data associated with the dynamically augmented relevance rankings for the plurality of trilateral inventory objects to provide a real-time rendering of the dynamically augmented relevance rankings for the plurality of trilateral inventory objects via an electronic interface of the consumer device.   
     
     
         29 . The computer program product of  claim 28 , further comprising instructions that when executed by the one or more computers cause the one or more computers to:
 configure a size of respective subranges from the set of subranges.   
     
     
         30 . The computer program product of  claim 28 , further comprising instructions that when executed by the one or more computers cause the one or more computers to:
 configure a size of the set of subranges based at least in part on a number of trilateral inventory objects respectively included in subranges from the set of subranges.   
     
     
         31 . The computer program product of  claim 28 , further comprising instructions that when executed by the one or more computers cause the one or more computers to:
 calculate the boost scaling factor for the subrange based at least in part on historical performance data associated with the plurality of trilateral inventory objects.