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: Improved user interfaces and methods are provided for presenting item recommendations to a user when the user selects an item to add to a shopping cart. In response to the user's selection, a page generation process generates and returns a page that includes a plurality of recommendations sections, each of which displays item recommendations generated using a different respective recommendation or selection algorithm (e.g., recommendations based on shopping cart contents, recommendations based on purchase history, etc.). These recommendation algorithms may be selected based on collected information regarding the user. The page may also include a shopping cart section which displays contents of the shopping cart.

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 displays the contents of the shopping cart, but omits some of the item information and/or controls provided on a shopping cart page, thereby preserving more screen real estate for the display of item recommendations. The condensed shopping cart portion also includes a link to the shopping cart page.

Abstract: A computer-implemented recommendation service uses item-to-item relationship mappings to select items to recommend to the user. The item-to-item relationship mappings may reflect user-behavior-based (e.g., purchase-based) item relationships, content-based item relationships, or a combination thereof. In one embodiment, personalized recommendations are generated for a user by a process that comprises retrieving from the mapping, for each of a plurality of items of interest to the user, a respective related items list; weighting the related items lists based on information regarding the user's affinity for the corresponding items of interest; combining the weighted related items lists to form a pool of scored items, and selecting items from the pool to recommend to the user.

Abstract: A computer-implemented recommendation service uses item-to-item relationship mappings to select items to recommend to the user. The item-to-item relationship mappings may reflect user-behavior-based (e.g., purchase-based) item relationships, content-based item relationships, or a combination thereof. In one embodiment, personalized recommendations are generated for a user by a process that comprises retrieving from the mapping, for each of a plurality of items of interest to the user, a respective related items list; weighting the related items lists based on information regarding the user's affinity for the corresponding items of interest; combining the weighted related items lists to form a pool of scored items, and selecting items from the pool to recommend 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.

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 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 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: 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 displays the contents of the shopping cart, but omits some of the item information and/or controls provided on a shopping cart page, thereby preserving more screen real estate for the display of item recommendations. The condensed shopping cart portion also includes a link to the shopping cart page.

Abstract: An improved user interfaces and methods are provided for presenting item recommendations to a user when the user selects an item to add to a shopping cart. In response to the user's selection, a page generation process generates and returns a page that includes a plurality of recommendations sections, each of which displays item recommendations generated using a different respective recommendation or selection algorithm (e.g., recommendations based on shopping cart contents, recommendations based on purchase history, etc.). These recommendation algorithms may be selected based on collected information regarding the user. The page may also include a shopping cart section which displays contents of the shopping cart.

Abstract: A system and process are disclosed for encoding selected data structures in browser cookies. The data structures may contain a variety of different types of data elements, including N-bit integers and other non-character elements. A version tracking scheme provides forward and backward compatibility between client and server software. The process is implemented without the need for any browser extensions, and without the need for users to download any special code to their computers.

Abstract: An improved user interface and method are provided for presenting recommendations to a user when the user adds an item to a shopping cart. In response to the shopping cart add event, a page generation process generates and returns a page that includes a recommendations portion and a condensed view of the shopping cart. The recommendations portion preferably includes multiple recommendation sections, each of which displays a different respective set of recommended items selected according to a different respective recommendation or selection algorithm (e.g., recommendations based on shopping cart contents, recommendations based on purchase history, etc.). The condensed shopping cart view preferably lacks controls for editing the shopping cart, and lacks certain types of product information, making more screen real estate available for the display of the recommendations content. A link to a full shopping cart page allows the user to edit the shopping cart and view expanded product descriptions.

Abstract: A system and process are disclosed for encoding selected data structures in browser cookies. The data structures may contain a variety of different types of data elements, including N-bit integers and other non-character elements. A version tracking scheme provides forward and backward compatibility between client and server software. The process is implemented without the need for any browser extensions, and without the need for users to download any special code to their computers.

Abstract: A system and process are disclosed for encoding selected data structures in browser cookies. The data structures may contain a variety of different types of data elements, including N-bit integers and other non-character elements. A version tracking scheme provides forward and backward compatibility between client and server software. The process is implemented without the need for any browser extensions, and without the need for users to download any special code to their computers.

Abstract: A system and process are disclosed for encoding selected data structures in browser cookies. The data structures may contain a variety of different types of data elements, including N-bit integers and other non-character elements. A version tracking scheme provides forward and backward compatibility between client and server software. The process is implemented without the need for any browser extensions, and without the need for users to download any special code to their computers.

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.

Abstract: A web site system implements a process for storing selected data structures within browser cookies. The data structures may contain a variety of different types of data elements, including N-bit integers and other non-character elements. A version tracking scheme provides forward and backward compatibility between client and server software. The process is implemented without the need for any browser extensions, and without the need for users to download any special code to their computers.

Abstract: A web site system implements a process for storing selected data structures within browser cookies. The data structures may contain a variety of different types of data elements, including N-bit integers and other non-character elements. A version tracking scheme provides forward and backward compatibility between client and server software. The process is implemented without the need for any browser extensions, and without the need for users to download any special code to their computers.

Abstract: An improved user interface and method are provided for presenting recommendations to a user when the user adds an item to a shopping cart. In response to the shopping cart add event, a page generation process generates and returns a page that includes a recommendations portion and a condensed view of the shopping cart. The recommendations portion preferably includes multiple recommendation sections, each of which displays a different respective set of recommended items selected according to a different respective recommendation or selection algorithm (e.g., recommendations based on shopping cart contents, recommendations based on purchase history, etc.). The condensed shopping cart view preferably lacks controls for editing the shopping cart, and lacks certain types of product information, making more screen real estate available for the display of the recommendations content. A link to a full shopping cart page allows the user to edit the shopping cart and view expanded product descriptions.