Method, medium, and system for providing a recommendation of a media item

Abstract

Providing a recommendation of a media item. Media item identifiers and corresponding nonzero media item attribute strengths for a target media item attribute are retrieved from a database. Each of the retrieved media item attribute strengths are randomized, resulting in randomized media item attribute strengths. One of the media item identifiers is selected according to predetermined selection criteria. A recommendation of a media item corresponding to the selected media item identifier is transmitted to a user device over a network.

1 . A method for providing a recommendation of a media item, the method comprising:
 retrieving, from a database, media item identifiers and corresponding nonzero media item attribute strengths for a target media item attribute;   randomizing each of the retrieved media item attribute strengths, resulting in randomized media item attribute strengths;   selecting, according to predetermined selection criteria, one of the media item identifiers; and   transmitting, to a user device over a network, a recommendation of a media item corresponding to the selected media item identifier.   
     
     
         2 . The method of  claim 1 , wherein the selecting step comprises at least one of selecting a media item identifier corresponding to a maximum of the randomized media item attribute strengths, and selecting a media item identifier corresponding to a randomized media item attribute strength closest in value to a media item attribute strength of the target media item attribute. 
     
     
         3 . The method of  claim 2 , wherein randomizing an attribute strength includes applying a random number to the attribute strength by performing an arithmetical calculation. 
     
     
         4 . The method of  claim 1 , wherein the user device includes at least one of a personal computer, a laptop computer, a television, a phone and a portable media player. 
     
     
         5 . The method of  claim 1 , further comprising:
 identifying a plurality of media item recommendations for a target user, wherein the plurality of media item recommendations correspond to a plurality of media item identifiers;   computing, for each of the plurality of media item identifiers, a total number of occurrences of the media item identifier; and   transmitting, to the user device, a media item recommendation of a media item identifier corresponding to a highest value of the total numbers of occurrences.   
     
     
         6 . The method of  claim 1 , further comprising:
 identifying a plurality of recommended media items for a target user by performing a plurality of iterations of at least one of the steps of  claim 1 .   
     
     
         7 . The method of  claim 1 , further comprising:
 retrieving, from the database, attributes that correspond to the selected media item identifier and corresponding nonzero additional media item attribute strengths;   randomizing each of the retrieved additional media item attribute strengths corresponding to the selected medium item identifier, resulting in additional randomized media item attribute strengths;   selecting, according to predetermined selection criteria, one of the retrieved attributes;   retrieving, from the database, additional media item identifiers and corresponding nonzero media item attribute strengths for the selected media item attribute;   randomizing each of the retrieved media item attribute strengths for the selected media item attribute, resulting in randomized media item attribute strengths for the selected media item attribute;   selecting, according to predetermined selection criteria, one of the additional media item identifiers; and   transmitting, to a user device over a network, a recommendation of a media item corresponding to the selected one of the additional media item identifiers.   
     
     
         8 . The method of  claim 7 , further comprising identifying a plurality of recommended media items for a target user by performing a plurality of iterations of at least one of the steps of  claim 7 . 
     
     
         9 . A system for providing a recommendation of a media item, the system including at least one processor operable to:
 retrieve, from a database, media item identifiers and corresponding nonzero media item attribute strengths for a target media item attribute;   randomize each of the retrieved media item attribute strengths, resulting in randomized media item attribute strengths;   select, according to predetermined selection criteria, one of the media item identifiers; and   transmit, to a user device over a network, a recommendation of a media item corresponding to the selected media item identifier.   
     
     
         10 . The system of  claim 9 , wherein the selecting step comprises at least one of selecting a media item identifier corresponding to a maximum of the randomized media item attribute strengths, and selecting a media item identifier corresponding to a randomized media item attribute strength closest in value to a media item attribute strength of the target media item attribute. 
     
     
         11 . The system of  claim 10 , wherein randomizing an attribute strength includes applying a random number to the attribute strength by performing an arithmetical calculation. 
     
     
         12 . The system of  claim 9 , wherein the user device includes at least one of a personal computer, a laptop computer, a television, a phone and a portable media player. 
     
     
         13 . The system of  claim 9 , wherein the at least one processor is further operable to:
 identify a plurality of media item recommendations for a target user, wherein the plurality of media item recommendations correspond to a plurality of media item identifiers;   compute, for each of the plurality of media item identifiers, a total number of occurrences of the media item identifier; and   transmit, to the user device, a media item recommendation of a media item identifier corresponding to a highest value of the total numbers of occurrences.   
     
     
         14 . The system of  claim 9 , wherein the at least one processor is further operable to:
 identify a plurality of recommended media items for a target user by performing a plurality of iterations of at least one of the steps of  claim 9 .   
     
     
         15 . The system of  claim 9 , wherein the at least one processor is further operable to:
 retrieve, from the database, attributes that correspond to the selected media item identifier and corresponding nonzero additional media item attribute strengths;   randomize each of the retrieved additional media item attribute strengths corresponding to the selected medium item identifier, resulting in additional randomized media item attribute strengths;   select, according to predetermined selection criteria, one of the retrieved attributes;   retrieve, from the database, additional media item identifiers and corresponding nonzero media item attribute strengths for the selected media item attribute;   randomize each of the retrieved media item attribute strengths for the selected media item attribute, resulting in randomized media item attribute strengths for the selected media item attribute; select, according to predetermined selection criteria, one of the additional media item identifiers; and   transmit, to a user device over a network, a recommendation of a media item corresponding to the selected one of the additional media item identifiers.   
     
     
         16 . The system of  claim 15 , wherein the at least one processor is further operable to identify a plurality of recommended media items for a target user by performing a plurality of iterations of at least one of the steps of  claim 15 . 
     
     
         17 . A computer-readable medium having stored thereon sequences of instructions, the sequences of instructions including instructions, which, when executed by one or more processors, cause the one or more processors to perform:
 retrieving, from a database, media item identifiers and corresponding nonzero media item attribute strengths for a target media item attribute;   randomizing each of the retrieved media item attribute strengths, resulting in randomized media item attribute strengths;   selecting, according to predetermined selection criteria, one of the media item identifiers; and   transmitting, to a user device over a network, a recommendation of a media item corresponding to the selected media item identifier.   
     
     
         18 . The computer-readable medium of  claim 17 , wherein the selecting step comprises at least one of selecting a media item identifier corresponding to a maximum of the randomized media item attribute strengths, and selecting a media item identifier corresponding to a randomized media item attribute strength closest in value to a media item attribute strength of the target media item attribute. 
     
     
         19 . The computer-readable medium of  claim 18 , wherein randomizing an attribute strength includes applying a random number to the attribute strength by performing an arithmetical calculation. 
     
     
         20 . The computer-readable medium of  claim 19 , wherein the user device includes at least one of a personal computer, a laptop computer, a television, a phone and a portable media player.