Personalized recommendations of items represented within a database
First Claim
1. A method of recommending items to users from a database of items, the method comprising:
- maintaining item selection histories of each of a plurality of users of a server system that provides functionality for browsing and selecting items from an electronic catalog of items, each item selection history corresponding to, and identifying items selected by, a particular user;
collectively analyzing at least the item selection histories of the plurality of users, as collected over a period of time, in an off-line processing mode to generate a plurality of data values that represent degrees to which specific items in the electronic catalog are related;
storing a selected subset of the plurality of data values in a mapping structure that maps items to related items; and
for each of a plurality of users of the electronic catalog, using the mapping structure, including the data values stored therein, to generate personalized recommendations of items within the catalog.
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Abstract
A computer-implemented service recommends items to a user based on items previously selected by the user, such as items previously purchased, viewed, or placed in an electronic shopping cart by the user. The items may, for example, be products represented within a database of an online merchant. In one embodiment, the service generates the recommendations using a previously generated table that maps items to respective lists of “similar” items. To generate the table, historical data indicative of users'"'"' affinities for particular items is processed periodically to identify correlations between item interests of users (e.g., items A and B are similar because a large portion of those who selected A also selected B). Personal recommendations are generated by accessing the table to identify items similar to those selected by the user. In one embodiment, items are recommended based on the current contents of a user'"'"'s shopping cart.
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Citations
52 Claims
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1. A method of recommending items to users from a database of items, the method comprising:
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maintaining item selection histories of each of a plurality of users of a server system that provides functionality for browsing and selecting items from an electronic catalog of items, each item selection history corresponding to, and identifying items selected by, a particular user; collectively analyzing at least the item selection histories of the plurality of users, as collected over a period of time, in an off-line processing mode to generate a plurality of data values that represent degrees to which specific items in the electronic catalog are related; storing a selected subset of the plurality of data values in a mapping structure that maps items to related items; and for each of a plurality of users of the electronic catalog, using the mapping structure, including the data values stored therein, to generate personalized recommendations of items within the catalog. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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25. A computer-implemented method of generating a mapping of items to related items, the method comprising:
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maintaining item selection histories of each of a plurality of users of a server system that provides functionality for browsing and selecting items from an electronic catalog of items, each item selection history corresponding to, and identifying items selected by, a particular user; collectively and programmatically analyzing the item selection histories of the plurality of users to generate a data value that represents a degree to which a first item and a second item in the catalog are related, wherein the data value is dependent upon at least (a) a number of users that selected both the first item and the second item, (b) a total number of users that selected the first item, and (c) a total number of users that selected the second item; and using the data value to determine whether the first item should be mapped to the second item in a mapping structure that maps items to related items. - View Dependent Claims (26, 27, 28)
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29. A computer-implemented method of recommending items to users of a server system that provides functionality for selecting items represented in an electronic catalog, the method comprising:
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identifying a plurality of items that are currently selected by a target user to obtain from an online business entity, including multiple items currently represented in a user-specific data repository in which item selections are maintained persistently over multiple sessions; identifying a set of additional items to recommend to the target user according to a selection algorithm in which a candidate item is considered for inclusion in the set based at least in-part upon a degree to which the candidate item is related to each of said plurality of items currently selected by the target user to obtain; and recommending at least some of the additional items in the set to the target user while the plurality of items are selected by the target user to obtain. - View Dependent Claims (30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41)
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42. A data mining method, comprising:
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programmatically analyzing user activity data associated with a plurality of users of an electronic catalog, in an off-line processing mode, to generate data values representing degrees to which specific catalog items are related to one another, said user activity data reflecting user interest in specific catalog items; using the data values to select, for each of a plurality of the catalog items, a corresponding set of related catalog items; generating mappings of said plurality of catalog items to the corresponding sets of related catalog items, wherein generating the mappings comprises storing selected ones of said data values, together with associated item identifiers, in a mapping data structure; and programmatically generating personalized item recommendations for each of a plurality of target users of the electronic catalog using said data values stored in the mapping data structure and using said mappings, wherein the personalized item recommendations are generated for each of the plurality of target users without updating the mapping data structure. - View Dependent Claims (43, 44, 45, 46, 47, 48, 49, 50)
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51. A data mining method, comprising:
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programmatically analyzing user activity data associated with a plurality of users of an electronic catalog, in an off-line processing mode, to generate data values representing degrees to which specific catalog items are related to one another, said user activity data reflecting user interest in specific catalog items; using the data values to select, for each of a plurality of the catalog items, a corresponding set of related catalog items; generating mappings of said plurality of catalog items to the corresponding sets of related catalog items; and programmatically generating personalized item recommendations for each of a plurality of users of the electronic catalog using said mappings; wherein programmatically generating personalized item recommendations comprises using the mappings, in combination with an item ratings profile of a target user, to select catalog items to recommend to the target user, wherein the item ratings profile comprises scores explicitly assigned to specific items by the target user.
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52. A data mining method, comprising:
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programmatically analyzing user activity data associated with a plurality of users of an electronic catalog, in an off-line processing mode, to generate data values representing degrees to which specific catalog items are related to one another, said user activity data reflecting user interest in specific catalog items; using the data values to select, for each of a plurality of the catalog items, a corresponding set of related catalog items; generating mappings of said plurality of catalog items to the corresponding sets of related catalog items; and programmatically generating personalized item recommendations for each of a plurality of users of the electronic catalog using said mappings; wherein programmatically generating personalized item recommendations comprises using the mappings to select catalog items that are related to a plurality of catalog items currently represented in a user-specific data repository in which item selections are maintained persistently over multiple sessions.
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Specification