Abstract: Various processes are disclosed for discovering item relationships between particular items, such as products represented in an electronic catalog, based on monitored user behaviors (e.g., item viewing activities, item purchases, shopping cart activities, etc.). The discovered item relationships may, for example, be used to generate personalized item recommendations for users, and/or to supplement item detail pages of an electronic catalog with lists of related items. Also disclosed are processes for generating personalized item recommendations based on users' search activities and browse node visits.

Abstract: Improved user interfaces and methods are provided for presenting item recommendations to a user when the user selects an item to add to an electronic shopping cart. In response to the user's selection, a page generation process generates and returns a page that includes a condensed shopping cart portion and a recommendations portion. The condensed shopping cart portion may include a link to an additional page that includes controls for editing the shopping cart and/or includes additional information regarding contents of the shopping cart. The recommendations portion may include multiple recommendations sections that are populated using different respective item selection methods.

Abstract: An interactive system enables users to generate and submit lists of items (e.g., products selected from an electronic catalog) for viewing by other users. The user-generated lists are selectively suggested to users of the system based (or based in part) on ratings of the user-generated lists. These ratings may, for example, be based on explicit ratings of the lists by users, and/or measures of how effective the respective lists are at driving purchases of items. In some contexts, the system may select one or more user-generated lists to present to a user based on a set of items purchased, viewed, or otherwise selected by the user, or based on the results of a search query submitted by the user.

Abstract: Electronic marketplaces offer a variety of items to customers over the Internet. Where two or more items are interchangeable with or equivalent to one another, such items may be utilized in the same applications and in the same manner, and marketed and sold together as interchanges or equivalents. Such items may be identified as interchangeable with or equivalent to one another based on a qualitative or quantitative score, which may consider any available information or attributes regarding the items, and may increase or decrease over time as the confidence in a determination of interchangeability or equivalence improves or declines. Moreover, such information or attributes may be identified from any source, such as sellers, vendors or manufacturers of the items, and qualitative or quantitative scores indicative of the accuracy or reliability of such information or attributes may be assigned to such sources, as well.

Abstract: A method is described for making a recommendation for an item. The method may include the operation of presenting a recommendation interface control to a user on a client device after the user has consumed an item. Using the recommendation interface control, the user then selects an individual and adds the name of the item the user consumed to the selected individual's recommendation list.

Abstract: Disclosed are various embodiments for the contextual indexing of applications using an application analyzer. In one embodiment, the application analyzer identifies at least one used element present in an application. The application analyzer computes a weight for the at least one used element, then provides the at least one used element and the respective weight to a contextual index service.

Abstract: A personalization network service enables developers to develop recommenders that can be made available to content site operators for providing recommendations to end users. The personalization network service may also be capable of optimizing the use and selection of the recommenders for different end users, groups or segments of end users, content sites, and the like.

Abstract: Disclosed are various embodiments for facilitating gift campaigns in a social networking system. An initiator of a gift campaign can select a recipient of a gift campaign as well as participants. Embodiments of the disclosure can facilitate selection of participants, collection of funds for the gift campaign and fulfillment of the gift to the recipient.

Abstract: Disclosed are various embodiments for selecting a subset of categories of product items to be used in merchandising. The subset of categories may be selected on a basis of a measured level of interest in the product items. Based on the subset of subcategories that have been selected, merchandising presentations may be automatically formulated and presented to a customer.

Abstract: A personalization network service enables developers to develop recommenders that can be made available to content site operators for providing recommendations to end users. The personalization network service may also be capable of optimizing the use and selection of the recommenders for different end users, groups or segments of end users, content sites, and the like.

Abstract: A personalization network service enables developers to develop recommenders that can be made available to content site operators for providing recommendations to end users. The personalization network service may also be capable of optimizing the use and selection of the recommenders for different end users, groups or segments of end users, content sites, and the like.

Abstract: Method and systems for providing item recommendations, displays categories (or tags) of recommended items where the categories are displayed using a quantity identifier indicative of the number of recommended items in that category. When a category is selected, a slide show viewer displays a number of items from the selected category.

Abstract: A computer-implemented service analyzes purchase histories and/or other types of behavioral data of users on an aggregated basis to detect and quantify associations between particular items represented in an electronic catalog. The detected associations are stored in a mapping structure that maps items to related items, and is used to recommend items to users of the electronic catalog. The items may include products and/or categories of products.

Abstract: Disclosed are various embodiments for defining subcategories of product items to be used in merchandising. The subcategories may be defined on the basis of product data and/or sales data for the product items. Based on a distribution of the product items in accordance with one or more of the product and/or sales data, implicit groups or subcategories can be identified and selected for merchandising purposes.

Abstract: Various computer-implemented services are disclosed for assisting users in selecting items from an electronic catalog, and for selecting merchants with which to conduct transactions. One such service enables users to share information about their respective purchases with other users. Another service enables users to share information regarding the merchants with which they have conducted transactions.

Abstract: A computer-implemented service analyzes purchase histories and/or other types of behavioral data of users on an aggregated basis to detect and quantify associations between particular items represented in an electronic catalog. The detected associations are stored in a mapping structure that maps items to related items, and is used to recommend items to users of the electronic catalog.

Abstract: A technology is described for making a recommendation for an item. An example method may include identifying a user interest in an item and identifying individuals that may have an interest in the item. The individuals may be presented to a user via a recommendation interface control that allows a name of the item to be added to a recommendation list for an individual selected from the individuals. An individual selected from the individual list to receive the recommendation may be identified and the name of the item may be added to the recommendation list for the individual.

Abstract: Systems and methods are disclosed for analyzing actions performed by users referred to a target site from particular referring sites or groups thereof, and for using the results of such analyses to select particular items to recommend to users. The referring sites may, for example, be affiliate sites that refer users to a merchant site in accordance with an affiliate marketing program.

Abstract: User content access events pertaining to a content item, such as an eBook, audio, video file, and so on, are collected and analyzed to determine progress data, including completion information about when the content item, or a portion thereof, has been completed. Once determined, further information or recommendations that have some relation to the completed content item may be presented to the user.

Abstract: A computer-implemented service analyzes purchase histories and/or other types of behavioral data of users on an aggregated basis to detect and quantify associations between particular items represented in an electronic catalog. The detected associations are stored in a mapping structure that maps items to related items, and is used to recommend items to users of the electronic catalog.