Cluster-based management of collections of items
First Claim
1. A computer-implemented method of generating personalized recommendations of items, the method comprising:
- maintaining an item collection of a user in computer storage, said item collection being a computer representation of a plurality of items selected by the user from an electronic catalog of items, wherein the items are represented in a hierarchical browse structure of said electronic catalog, said hierarchical browse structure comprising multiple levels of browse nodes;
applying a clustering algorithm to the item collection to subdivide the collection into multiple clusters of said items, said clusters generated based, at least in part, on calculated distances between the items in the hierarchical browse structure, said distances being dependent upon the browse nodes to which particular items are assigned;
outputting a visual representation of the multiple clusters for presentation to the user via a user interface that enables the user to rate specific clusters of items, said visual representation enabling the user to identify particular items included in each of said clusters;
receiving an indication of a cluster rating specified by the user via said user interface, said cluster rating corresponding to a cluster selected by the user from said visual representation, and representing a collective rating by said user of multiple items in said cluster;
generating personalized item recommendations for the user by execution of code modules by a computer system, wherein generating the personalized item recommendations comprises taking the cluster rating into consideration in selecting items from the item collection to use as recommendation sources, and by identifying, for recommendation to the user, additional items that are related to said recommendation source items, such that the personalized item recommendations are based on a selected subset of the item collection; and
outputting a representation of the personalized item recommendations for presentation to the user.
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Abstract
Computer-implemented processes are disclosed for clustering items and improving the utility of item recommendations. One process involves applying a clustering algorithm to a user'"'"'s collection of items. Information about the resulting clusters is then used to select items to use as recommendation sources. Another process involves displaying the clusters of items to the user via a collection management interface that enables the user to attach cluster-level metadata, such as by rating or tagging entire clusters of items. The resulting metadata may be used to improve the recommendations generated by a recommendation engine. Another process involves forming clusters of items in which a user has indicated a lack of interest, and using these clusters to filter the output of a recommendation engine. Yet another process involves applying a clustering algorithm to the output of a recommendation engine to arrange the recommended items into cluster-based categories for presentation to the user.
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Citations
41 Claims
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1. A computer-implemented method of generating personalized recommendations of items, the method comprising:
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maintaining an item collection of a user in computer storage, said item collection being a computer representation of a plurality of items selected by the user from an electronic catalog of items, wherein the items are represented in a hierarchical browse structure of said electronic catalog, said hierarchical browse structure comprising multiple levels of browse nodes; applying a clustering algorithm to the item collection to subdivide the collection into multiple clusters of said items, said clusters generated based, at least in part, on calculated distances between the items in the hierarchical browse structure, said distances being dependent upon the browse nodes to which particular items are assigned; outputting a visual representation of the multiple clusters for presentation to the user via a user interface that enables the user to rate specific clusters of items, said visual representation enabling the user to identify particular items included in each of said clusters; receiving an indication of a cluster rating specified by the user via said user interface, said cluster rating corresponding to a cluster selected by the user from said visual representation, and representing a collective rating by said user of multiple items in said cluster; generating personalized item recommendations for the user by execution of code modules by a computer system, wherein generating the personalized item recommendations comprises taking the cluster rating into consideration in selecting items from the item collection to use as recommendation sources, and by identifying, for recommendation to the user, additional items that are related to said recommendation source items, such that the personalized item recommendations are based on a selected subset of the item collection; and outputting a representation of the personalized item recommendations for presentation to the user. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 32, 33, 34, 35, 36, 37, 38, 39)
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15. A computer system, comprising:
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a computer data repository that stores a collection of items associated with a user, said collection of items comprising a computer representation of a plurality of items selected by the user from an electronic catalog of items, wherein the items are arranged in the electronic catalog according to a hierarchical browse structure that has multiple levels of browse nodes; a clustering component that is operative to apply a clustering algorithm to the collection of items to divide the collection into multiple clusters of items, said clustering component operative to generate the clusters based at least partly on distances between particular items in the hierarchical browse structure, said distances being dependent upon the browse nodes to which the items are assigned; a collection management interface that includes functionality for the user to view the clusters of items, and to visualize assignments of particular items to particular clusters, said cluster management interface additionally providing functionality for the user to assign a cluster rating to a cluster to thereby collectively rate a plurality of items included in said cluster; and a recommendation system that is operative to use at least said cluster rating to select, from said collection of items, a subset of items to use as recommendation sources, and to use said subset of items to generate personalized item recommendations for the user, such that the personalized item recommendations are based on less than all of the items of the item collection, said recommendation system comprising computer hardware. - View Dependent Claims (16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 40, 41)
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Specification