US2023024574A1PendingUtilityA1

Methods and apparatus to generate recommendations based on attribute vectors

Assignee: GRACENOTE INCPriority: Nov 25, 2019Filed: Nov 17, 2020Published: Jan 26, 2023
Est. expiryNov 25, 2039(~13.3 yrs left)· nominal 20-yr term from priority
G06F 16/639G06F 16/635G06F 16/686G06Q 30/0631G06F 16/2237
50
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Claims

Abstract

Methods and apparatus are disclosed to generate a recommendation, including an attribute vector aggregator to form a resultant attribute vector based on an input set of attribute vectors, the set of attribute vectors containing at least one of a media attribute vector, an attendee attribute vector, an artist attribute vector, an event attribute vector, or a venue attribute vector, and a recommendation generator, the recommendation generator including: a vector comparator to perform a comparison between an input attribute vector and other attribute vectors and a recommendation compiler to create one or more recommendations of at least one of media, an artist, an event, or a venue based on the comparison.

Claims

exact text as granted — not AI-modified
1 - 28 . (canceled) 
     
     
         29 . An apparatus comprising:
 one or more memories;   instructions; and   processor circuitry to execute the instructions to at least:
 determine (a) a first result vector based on a first comparison of a query attribute vector and a first attribute vector and (b) a second result vector based on a second comparison of the query attribute vector and a second attribute vector, the query attribute vector based on one or more attribute vectors associated with a media player of a device; 
 apply (c) a first weight vector to the first result vector to determine a first weighted result vector and (d) a second weight vector to the second result vector to determine a second weighted result vector, the first weight vector corresponding to the first attribute vector, the second weight vector corresponding to the second attribute vector; 
 determine a first scalar value representative of the first weighted result vector and a second scalar value representative of the second weighted result vector; and 
 cause transmission of a recommendation associated with media to the device, the recommendation based on ordering of the first scalar value or the second scalar value. 
   
     
     
         30 . The apparatus of  claim 29 , wherein the processor circuitry is to generate the first weight vector and the second weight vector, the first weight vector and the second weight vector based on a trend associated with the one or more attribute vectors associated with the media player of the device. 
     
     
         31 . The apparatus of  claim 29 , wherein the processor circuitry is to:
 access descriptive information associated with the media player of the device;   access a third attribute vector and a fourth attribute vector based on the descriptive information; and   aggregate the third attribute vector and the fourth attribute vector to generate the query attribute vector.   
     
     
         32 . The apparatus of  claim 31 , wherein to aggregate the third attribute vector and the fourth attribute vector, the processor circuitry is to:
 assign a first scalar weight to the third attribute vector to determine a third weighted attribute vector;   apply a second scalar weight to the fourth attribute vector to determine a fourth weighted attribute vector; and   determine a weighted average of the third weighted attribute vector and the fourth weighted attribute vector.   
     
     
         33 . The apparatus of  claim 29 , wherein the recommendation associated with the media is based on a lower one of the first scalar value or the second scalar value. 
     
     
         34 . The apparatus of  claim 29 , wherein the recommendation associated with the media includes a playlist that identifies a first media sample associated with the first attribute vector and a second media sample associated with the second attribute vector. 
     
     
         35 . The apparatus of  claim 29 , wherein the recommendation associated with the media identifies at least one a song, an artist, an event, a playlist, or a venue. 
     
     
         36 . At least one non-transitory computer readable medium comprising instructions that, when executed, cause processor circuitry to at least:
 determine (a) a first result vector based on a first comparison of a query attribute vector and a first attribute vector and (b) a second result vector based on a second comparison of the query attribute vector and a second attribute vector, the query attribute vector based on one or more attribute vectors associated with a media player of a device;   apply (c) a first weight vector to the first result vector to determine a first weighted result vector and (d) a second weight vector to the second result vector to determine a second weighted result vector, the first weight vector corresponding to the first attribute vector, the second weight vector corresponding to the second attribute vector;   determine a first scalar value representative of the first weighted result vector and a second scalar value representative of the second weighted result vector; and   cause transmission of a recommendation associated with media to the device, the recommendation based on ordering of the first scalar value or the second scalar value.   
     
     
         37 . The at least one non-transitory computer readable medium of  claim 36 , wherein the instructions, when executed, cause the processor circuitry generate the first weight vector and the second weight vector, the first weight vector and the second weight vector based on a trend associated with the one or more attribute vectors associated with the media player of the device. 
     
     
         38 . The at least one non-transitory computer readable medium of  claim 36 , wherein the instructions, when executed, cause the processor circuitry:
 access descriptive information associated with the media player of the device;   access a third attribute vector and a fourth attribute vector based on the descriptive information; and   aggregate the third attribute vector and the fourth attribute vector to generate the query attribute vector.   
     
     
         39 . The at least one non-transitory computer readable medium of  claim 38 , wherein to aggregate the third attribute vector and the fourth attribute vector, the instructions, when executed, cause the processor circuitry:
 assign a first scalar weight to the third attribute vector to determine a third weighted attribute vector;   apply a second scalar weight to the fourth attribute vector to determine a fourth weighted attribute vector; and   determine a weighted average of the third weighted attribute vector and the fourth weighted attribute vector.   
     
     
         40 . The at least one non-transitory computer readable medium of  claim 36 , wherein the recommendation associated with the media is based on a lower one of the first scalar value or the second scalar value. 
     
     
         41 . The at least one non-transitory computer readable medium of  claim 36 , wherein the recommendation associated with the media includes a playlist that identifies a first media sample associated with the first attribute vector and a second media sample associated with the second attribute vector. 
     
     
         42 . The at least one non-transitory computer readable medium of  claim 36 , wherein the recommendation associated with the media identifies at least one a song, an artist, an event, a playlist, or a venue. 
     
     
         43 . A method comprising:
 determining (a) a first result vector based on a first comparison of a query attribute vector and a first attribute vector and (b) a second result vector based on a second comparison of the query attribute vector and a second attribute vector, the query attribute vector based on one or more attribute vectors associated with a media player of a device;   applying, by executing an instruction with processor circuitry, (c) a first weight vector to the first result vector to determine a first weighted result vector and (d) a second weight vector to the second result vector to determine a second weighted result vector, the first weight vector corresponding to the first attribute vector, the second weight vector corresponding to the second attribute vector;   determining, by executing an instruction with the processor circuitry, a first scalar value representative of the first weighted result vector and a second scalar value representative of the second weighted result vector; and   transmitting a recommendation associated with media to the device, the recommendation based on ordering of the first scalar value or the second scalar value.   
     
     
         44 . The method of  claim 43 , further including generating the first weight vector and the second weight vector, the first weight vector and the second weight vector based on a trend associated with the one or more attribute vectors associated with the media player of the device. 
     
     
         45 . The method of  claim 43 , further including:
 accessing descriptive information associated with the media player of the device;   accessing a third attribute vector and a fourth attribute vector based on the descriptive information; and   aggregating the third attribute vector and the fourth attribute vector to generate the query attribute vector.   
     
     
         46 . The method of  claim 45 , wherein aggregating the third attribute vector and the fourth attribute vector includes:
 assigning a first scalar weight to the third attribute vector to determine a third weighted attribute vector;   applying a second scalar weight to the fourth attribute vector to determine a fourth weighted attribute vector; and   determining a weighted average of the third weighted attribute vector and the fourth weighted attribute vector.   
     
     
         47 . The method of  claim 43 , wherein the recommendation associated with the media is based on a lower one of the first scalar value or the second scalar value. 
     
     
         48 . The method of  claim 43 , wherein the recommendation associated with the media includes a playlist that identifies a first media sample associated with the first attribute vector and a second media sample associated with the second attribute vector. 
     
     
         49 . The method of  claim 43 , wherein the recommendation associated with the media identifies at least one a song, an artist, an event, a playlist, or a venue.

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