Method and apparatus for a ranking engine

Abstract

A computer-implemented method is provided for ranking files from an Internet search. In one embodiment, the method comprises assigning a score to each file based on at least one of the following factors: recency, editorial popularity, clickthru popularity, favorites metadata, or favorites collaborative filtering. The file may be organized based on the assigned scores to provide users with more accurate search results.

What is claimed is: 
     
         1 . A method comprising:
 maintaining a plurality of items associated with a user;   calculating, by at least one processor, a score for each item of the plurality of items, wherein calculating the score for a given item is based on at least positive indications by the user for the given item, positive indications for the given item by favored co-users of the user, and a total number of positive indications for the given item;   ranking plurality of items based on the score for each item; and   displaying items of the plurality of items according to the ranking.   
     
     
         2 . The method as recited in  claim 1 , further comprising calculating, by the at least one processor, the score for the given item based on the similarity of the given item to other items preferred by the user. 
     
     
         3 . The method as recited in  claim 1 , further comprising calculating, by the at least one processor, the score for the given item based on whether the user has shared the given item with other co-users. 
     
     
         4 . The method as recited in  claim 1 , further comprising calculating, by the at least one processor, the score for the given item based on the overall popularity of the given item. 
     
     
         5 . The method as recited in  claim 1 , further comprising calculating, by the at least one processor, the score for the given item based on the recency of the given item, wherein more recent items are given a higher score than less recent items. 
     
     
         6 . The method as recited in  claim 1 , further comprising calculating, by the at least one processor, the score for the given item based on user input in connection with the given item. 
     
     
         7 . The method as recited in  claim 1 , further comprising calculating, by the at least one processor, the score for the given item based on one of editorial popularity, clickthru popularity, collaborative filtering, and favored metadata. 
     
     
         8 . The method as recited in  claim 1 , further comprising weighting each factor when assigning scores to each item of the plurality of items. 
     
     
         9 . The method as recited in  claim 1 , further comprising:
 detecting a new item added to the plurality of items;   assigning a score for the new item;   re-ranking the plurality of items; and   refreshing the display of the items of the plurality of items according to the re-ranking of the plurality of items.   
     
     
         10 . The method as recited in  claim 1 , wherein the given item comprises a video file. 
     
     
         11 . A method comprising:
 maintaining a plurality of items associated with a user;   calculating, by at least one processor, a score for each item of the plurality of items wherein calculating the score for a given item is based on at least whether the user has provided a positive indication of the given item, the similarity of the given item to other items preferred by the user, and whether the user has shared the given item with other co-users;   ranking the plurality of items based on the score of each item; and   displaying items of the plurality of items according to the ranking.   
     
     
         12 . The method as recited in  claim 11 , further comprising calculating, by the at least one processor, the score for the given item based on one or more of a number of positive indications of the given item by favored co-users of the user and a total number of positive indications of the given item. 
     
     
         13 . The method as recited in  claim 12  further comprising calculating, by the at least one processor, the score for the given item based on the overall popularity of the given item. 
     
     
         14 . The method as recited in  claim 13 , further comprising calculating, by the at least one processor, the score for the given item based on the recency of the given item, wherein more recent items are given a higher score than less recent items. 
     
     
         15 . The method as recited in  claim 14 , further comprising calculating, by the at least one processor, the score for the given item based on the similarity of the given item to other items preferred by the user. 
     
     
         16 . The method as recited in  claim 15 , further comprising calculating, by the at least one processor, the score for the given item based on user input in connection with the given item. 
     
     
         17 . The method as recited in  claim 16 , further comprising calculating, by the at least one processor, the score for the given item based on one of editorial popularity, clickthru popularity, collaborative filtering, and favored metadata. 
     
     
         18 . The method as recited in  claim 10 , further comprising:
 detecting a new item added to the plurality of items;   assigning a score for the new item;   re-ranking the plurality of items; and   refreshing the display of the items of the plurality of items according to the re-ranking of the plurality of items.   
     
     
         19 . A system comprising:
 at least one processor; and   at least one non-transitory computer readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the system to:
 calculate a score for each item of the plurality of items, wherein the score for a given item is calculated based on at least positive indications by the user for the given item, positive indications for the given item by favored co-users of the user, and a total number of positive indications for the given item; 
 rank the plurality of items based on the score for each item; and 
 display items of the plurality of items according to the rank. 
   
     
     
         20 . The system as recited in  claim 19 , further comprising instructions that, when executed by the at least one processor cause the system to:
 detect a new item added to the plurality of items;   assign a score for the new item;   re-ranking the plurality of items; and   refresh the display of the items of the plurality of items according to the re-ranking of the plurality of items.