Abstract: A warehouse from which shoppers fulfill orders for an online concierge system maintains an online concierge system-specific portion for which the online concierge system specifies placement of items in regions. To place items in the online concierge system-specific portion, the online concierge system accounts for co-occurrences of different items in orders and measures of similarity between different items. From the co-occurrences of items, the online concierge system generates an affinity graph. The online concierge system also generates a colocation graph based on distances between different regions in the online concierge system-specific portion. Using an optimization function with the affinity graph and the colocation graph, the online concierge system selects regions within the online concierge system-specific portion for different items to minimize an amount of time for shoppers to obtain items in the online concierge-system specific portion.

Abstract: A warehouse from which shoppers fulfill orders for an online concierge system maintains an online concierge system-specific portion for which the online concierge system specifies placement of items in regions. To place items in the online concierge system-specific portion, the online concierge system accounts for co-occurrences of different items in orders and measures of similarity between different items. From the co-occurrences of items, the online concierge system generates an affinity graph. The online concierge system also generates a colocation graph based on distances between different regions in the online concierge system-specific portion. Using an optimization function with the affinity graph and the colocation graph, the online concierge system selects regions within the online concierge system-specific portion for different items to minimize an amount of time for shoppers to obtain items in the online concierge-system specific portion.

Abstract: A warehouse from which shoppers fulfill orders for an online concierge system maintains an online concierge system-specific portion for which the online concierge system specifies placement of items in regions. To place items in the online concierge system-specific portion, the online concierge system accounts for co-occurrences of different items in orders and measures of similarity between different items. From the co-occurrences of items, the online concierge system generates an affinity graph. The online concierge system also generates a colocation graph based on distances between different regions in the online concierge system-specific portion. Using an optimization function with the affinity graph and the colocation graph, the online concierge system selects regions within the online concierge system-specific portion for different items to minimize an amount of time for shoppers to obtain items in the online concierge-system specific portion.

Abstract: An online concierge system generates suggested instructions for presentation to a user. The online concierge system access instruction examples corresponding to a target item category and generates candidate instruction representations based on instruction messages within each instruction example. The online concierge system generates preliminary scores for the candidate instruction representations that are directly related to an intra-category frequency of use of the instruction tokens of the candidate instruction representation within the target item category. The online system normalizes these preliminary scores for the candidate instruction representations based on the inter-category frequency of use of the instruction tokens in all item categories to generate final scores for the candidate instruction representations. The online concierge system selects a set of instruction representations based on these final scores and generates suggested instructions based on the set of instruction representations.

Abstract: An item availability model produces item verification notifications, for example, by receiving data indicating a plurality of items associated with an online shopping concierge platform; determining based at least in part on the data indicating the plurality of items and one or more machine learning (ML) models, a subset of the plurality of items for which to have one or more shoppers associated with the online shopping concierge platform check current availability at one or more warehouse locations associated with the online shopping concierge platform; and generating and transmitting communications comprising at least one of dispatching, instructing, incentivizing, or encouraging the one or more shoppers to check the current availability of at least a portion of the subset of the plurality of items at the one or more warehouse locations.

Abstract: A warehouse from which shoppers fulfill orders for an online concierge system maintains an online concierge system-specific portion for which the online concierge system specifies placement of items in regions. To place items in the online concierge system-specific portion, the online concierge system accounts for co-occurrences of different items in orders and measures of similarity between different items. From the co-occurrences of items, the online concierge system generates an affinity graph. The online concierge system also generates a colocation graph based on distances between different regions in the online concierge system-specific portion. Using an optimization function with the affinity graph and the colocation graph, the online concierge system selects regions within the online concierge system-specific portion for different items to minimize an amount of time for shoppers to obtain items in the online concierge-system specific portion.

Abstract: A warehouse from which shoppers fulfill orders for an online concierge system maintains an online concierge system-specific portion for which the online concierge system specifies placement of items in regions. To place items in the online concierge system-specific portion, the online concierge system accounts for co-occurrences of different items in orders and measures of similarity between different items. From the co-occurrences of items, the online concierge system generates an affinity graph. The online concierge system also generates a colocation graph based on distances between different regions in the online concierge system-specific portion. Using an optimization function with the affinity graph and the colocation graph, the online concierge system selects regions within the online concierge system-specific portion for different items to minimize an amount of time for shoppers to obtain items in the online concierge-system specific portion.

Abstract: An online concierge system displays an ordering interface to users that displays items offered by various warehouses. The online concierge system includes machine learning availability model that estimates an item's availability and visually distinguishes items offered by a warehouse having less than a threshold availability from other items. Because information from a warehouse that an item that was out of stock is now in stock is often delayed, the online concierge system transmits a request to a shopper fulfilling an order to check for an item's availability at a warehouse. For example, the online concierge system allows users to include a request for an indication of an item's availability when placing an order. When the online concierge system receives a threshold number of requests for the item, the online concierge system prompts a shopper fulfilling an order including items near the item for the item's availability.

Abstract: An online concierge system allows users to add items to an order and provide instructions to a shopper specifying attributes for selecting an item in the order from a warehouse. To simplify entry of the instructions, the online concierge system converts previously received instructions comprising unstructured text into structured suggestions by extracting words from the previously received instructions. The suggestions are associated with items or generic item descriptions. When a user includes an item in an order, the online concierge system displays one or more suggestions associated with the item as selectable options in an interface to simplify specification of instructions for the item.

Abstract: A document system tracks activity within comment threads associated with portions of a stored document. When activity is detected within the document, the document system generates a corresponding notification for display by a client device within a notification interface. The notification interface displays one or more notifications, each associated with activity in documents stored by the document system, and orders the notifications by document, by date, by filter, or any other suitable factor. The user may assign a priority to each document or folder such that notifications associated with documents or folders with a higher priority are displayed before those associated with a lower priority. The notifications may include portions of comment threads, and a user can reply to a comment thread via a response element of the notification interface. The user's reply is incorporated into the comment thread and stored by the document system.

Abstract: A document system tracks activity within comment threads associated with portions of a stored document. When activity is detected within the document, the document system generates a corresponding notification for display by a client device within a notification interface. The notification interface displays one or more notifications, each associated with activity in documents stored by the document system, and orders the notifications by document, by date, by filter, or any other suitable factor. The user may assign a priority to each document or folder such that notifications associated with documents or folders with a higher priority are displayed before those associated with a lower priority. The notifications may include portions of comment threads, and a user can reply to a comment thread via a response element of the notification interface. The user's reply is incorporated into the comment thread and stored by the document system.

Abstract: A document system tracks activity within comment threads associated with portions of a stored document. When activity is detected within the document, the document system generates a corresponding notification for display by a client device within a notification interface. The notification interface displays one or more notifications, each associated with activity in documents stored by the document system, and orders the notifications by document, by date, by filter, or any other suitable factor. The user may assign a priority to each document or folder such that notifications associated with documents or folders with a higher priority are displayed before those associated with a lower priority. The notifications may include portions of comment threads, and a user can reply to a comment thread via a response element of the notification interface. The user's reply is incorporated into the comment thread and stored by the document system.

Abstract: A document system tracks activity within comment threads associated with portions of a stored document. When activity is detected within the document, the document system generates a corresponding notification for display by a client device within a notification interface. The notification interface displays one or more notifications, each associated with activity in documents stored by the document system, and orders the notifications by document, by date, by filter, or any other suitable factor. The user may assign a priority to each document or folder such that notifications associated with documents or folders with a higher priority are displayed before those associated with a lower priority. The notifications may include portions of comment threads, and a user can reply to a comment thread via a response element of the notification interface. The user's reply is incorporated into the comment thread and stored by the document system.