Abstract: An online recommendation system can choose recipes to recommend to a customer based on a set of ingredients the customer is inferred to have on hand (a customer pantry model). For example, the recommendation system can look at recent or historical purchases made by the customer and determine what items the customer still has available based on an assumed shelf life for the purchased items. Using the customer pantry model, the recommendation system selects recipes based on overlapping ingredients between recipe's ingredient lists and ingredients available to the customer (including the customer pantry model and their current shopping cart). In some implementations, the recommendation system first selects a set of candidate recipes based on the overlap, then selects the final set of recipes to recommend based on a score optimization (for example, performed using a machine learning model).

Abstract: An online concierge system receives, from a client device comprising a customer mobile application, an order comprising a list of one or more items for delivery to a destination location from a warehouse. The customer mobile application comprises a user interface. The online concierge system identifies a set of item groupings from a database that match the list of one or more items. The online concierge system applies the order and the set of item groupings to a machine learning model to produce a set of foundational items. The online concierge system sends for display, to the client device, an updated user interface comprising a foundational items graphical element that visually distinguishes the set of foundational items from other items in the list of one or more items.

Abstract: A shopping cart system detects the initiation of a shopping session within a physical retail store by a customer, in which the shopping cart system includes a shopping cart, a processor, a memory, and a set of sensors. Contextual information associated with the shopping cart received by the sensors during the shopping session is tracked, in which the contextual information describes one or more locations of the shopping cart within the store, a state of the shopping cart, and a set of items within the shopping cart. Responsive to identifying an opportunity to present content to the customer based on the contextual information, the system identifies a set of content items associated with one or more items within the store based on the contextual information. The system generates a user interface including the set of content items and sends the user interface to a display area associated with the customer.

Abstract: An online system receives information describing a physical retail store, in which the information includes attributes of physical elements within the store and their arrangement. A request is received from a user to generate a rendering of the store in a virtual reality environment. A profile of the user describing the user's geographic location and a set of historical actions performed by the user are accessed, in which the set of historical actions is associated with one or more of the physical elements. Based on the information describing the store and the profile, the rendering is generated to include virtual reality elements representing a set of the physical elements arranged based on the arrangement of the physical elements, and the rendering is sent for display to the user. When an update to the information describing the store is received, the rendering is updated and sent for display to the user.

Abstract: An online concierge system determines an emotion of a user from inputs received from the user and other contextual information about a user to select items to identify to the user for an order. The online concierge system logs historical data about items included in orders by the user and corresponding emotions of the user and contextual information for the user when the items were included in orders. Subsequently, when the user requests to create an order, the online concierge system determines an emotion for the user and contextual information for the user and selects one or more items included in prior orders when the user had the same emotion and had similar contextual information. The online concierge system transmits information describing one or more of the selected items to a client device of the user for presentation.

Abstract: An online concierge system determines customer preferences based on physical store patterns of the customer and provides search results based on the customer preferences during an online customer ordering session. The online concierge system may obtain customer location data while the customer is shopping in a physical warehouse. The online concierge system maps the customer location data to a warehouse floorplan layout. Based on the locations visited and the time spend at each location in the warehouse, the online concierge system determines that the customer is interested in certain types of items. The online concierge system may use the customer preferences to suggest items during online ordering sessions.

Abstract: An online recommendation system can choose recipes to recommend to a customer based on a set of ingredients the customer is inferred to have on hand (a customer pantry model). For example, the recommendation system can look at recent or historical purchases made by the customer and determine what items the customer still has available based on an assumed shelf life for the purchased items. Using the customer pantry model, the recommendation system selects recipes based on overlapping ingredients between recipe's ingredient lists and ingredients available to the customer (including the customer pantry model and their current shopping cart). In some implementations, the recommendation system first selects a set of candidate recipes based on the overlap, then selects the final set of recipes to recommend based on a score optimization (for example, performed using a machine learning model).

Abstract: The present disclosure provides a system and method for analyzing customer communications to provide better customer service including generating customer related data from communications of a customer by at least one sensing device located in a venue, transmitting the generated customer related data to an analysis engine, determining based on an analysis of the customer related data a customer experience, identifying at least one suggestion to provide better customer service including the identification of a representative of the venue that the analysis engine has determined can assist the customer, and receiving the at least one suggestion including an indication that the representative should assist the customer from the analysis engine by a computing device associated with the representative of the venue.

Abstract: A first indication from a user is received. The indication includes a task to be performed using at least one application programming interface. A machine learning model is determine. At least one application programming interface is determined using the machine learning model and the request. The at least one application programming interface is provided to the user.

Abstract: For a portal server system for managing a collection of associated portlets responsive to user requests to access a application, the invention provides apparatus and methodology including: a portlet application session object for saving parameters from user requests of associated portlets; and, a portlet application communication client linked to said portlet application session means for communicating between said associated portlets and said web application to convey user requests received from said associated portlets to said web application.

Abstract: A method and system for improving an automated mobile device detection system is provided. The method includes automatically detecting Web pages being accessed by a user via a mobile hardware device. Movement based attributes, biological parameters, and a geographical location of the user are detected via hardware sensors of the mobile device. The Webpages are modified such that a modified plurality of Webpages is generated based on the analysis. The modified plurality of Webpages is presented to the user.

Abstract: A method for implementing a graphical modeling tool in a web-based environment is disclosed herein. In one embodiment, such a method may include enabling a user to import, into a web-based environment, a domain meta model comprising a number of meta model elements. The method may further enable the user to associate the meta model elements with graphical representations in the web-based environment, thereby allowing the user to create palette elements. The user may then assemble the palette elements on a canvas to create a diagram. This diagram may be converted into an instance of the domain meta model. This instance may be validated for conformance with the rules and constraints associated with the domain meta model. A corresponding apparatus and computer program product are also disclosed and claimed herein.

Abstract: In an approach to automated merchandising, one or more computer processors detect access to an electronic store by a user. The one or more computer processors determine a location of the user. The one or more computer processors retrieve a plurality of social media communications associated with the location of the user, where social media communications include one or more publically available entries made by one or more users of one or more social media applications. The one or more computer processors determine whether the retrieved social media communications are associated with one or more merchandise associated with the electronic store. In response to determining the retrieved social media communications are associated with the one or more merchandise associated with the electronic store, the one or more computer processors determine a position of the one or more merchandise in one or more communication channels.

Abstract: Managing product acquisition based on product characteristics is provided. Characteristics of a product in an electronic shopping cart are determined based on product provider data and product data corresponding to the product. A number of product characteristic points for the product in the electronic shopping cart is calculated based on mapping the determined characteristics of the product to user-defined product points. It is determined whether the calculated number of product characteristic points for the product in the shopping cart is less than or equal to a user-defined product characteristic point budget. In response to determining that the calculated number of product characteristic points for the product in the shopping cart is greater than the user-defined product characteristic point budget, a warning is displayed on a user client device that the user-defined product characteristic point budget is exceeded.

Abstract: Aspects of the present invention provide devices that receive a request for digital content, the digital content request includes a list of vendor-object pairs, each object in the vendor-object pairs is identified in requested digital content, and each object in the vendor-object pairs includes a request for vending of the object from a corresponding vendor in the vendor-object pairs. The devices determine acceptance of the digital content request to offer vending of one or more objects in the vendor-object pairs, and send a vendor response, which offers the vending of the one or more objects in the vendor-object pairs.

Abstract: Managing product acquisition based on product characteristics is provided. Characteristics of a product in an electronic shopping cart are determined based on product provider data and product data corresponding to the product. A number of product characteristic points for the product in the electronic shopping cart is calculated based on mapping the determined characteristics of the product to user-defined product points. It is determined whether the calculated number of product characteristic points for the product in the shopping cart is less than or equal to a user-defined product characteristic point budget. In response to determining that the calculated number of product characteristic points for the product in the shopping cart is greater than the user-defined product characteristic point budget, a warning is displayed on a user client device that the user-defined product characteristic point budget is exceeded.

Abstract: An illustrative embodiment of a computer-implemented process for dynamic management of integration protocols connects a set of applications to a communication fabric to form a set of connections, which are monitored to collect a set of performance metrics. In response to a determination the predetermined performance metric is not within the predetermined tolerance associated with the particular application in the set of applications an integration path in the set of connections for the particular application in the set of applications is adjusted by programmatically using a set of rules wherein each rule in the set of rules is a performance driven rule.

Abstract: A method and system for improving an automated mobile device detection system is provided. The method includes automatically detecting Web pages being accessed by a user via a mobile hardware device. Movement based attributes, biological parameters, and a geographical location of the user are detected via hardware sensors of the mobile device. The Webpages are modified such that a modified plurality of Webpages is generated based on the analysis. The modified plurality of Webpages is presented to the user.

Abstract: Managing product acquisition based on product characteristics is provided. Characteristics of a product in an electronic shopping cart are determined based on product provider data and product data corresponding to the product. A number of product characteristic points for the product in the electronic shopping cart is calculated based on mapping the determined characteristics of the product to user-defined product points. It is determined whether the calculated number of product characteristic points for the product in the shopping cart is less than or equal to a user-defined product characteristic point budget. In response to determining that the calculated number of product characteristic points for the product in the shopping cart is greater than the user-defined product characteristic point budget, a warning is displayed on a user client device that the user-defined product characteristic point budget is exceeded.

Abstract: Managing product acquisition based on product characteristics is provided. Characteristics of a product in an electronic shopping cart are determined based on product provider data and product data corresponding to the product. A number of product characteristic points for the product in the electronic shopping cart is calculated based on mapping the determined characteristics of the product to user-defined product points. It is determined whether the calculated number of product characteristic points for the product in the shopping cart is less than or equal to a user-defined product characteristic point budget. In response to determining that the calculated number of product characteristic points for the product in the shopping cart is greater than the user-defined product characteristic point budget, a warning is displayed on a user client device that the user-defined product characteristic point budget is exceeded.