Abstract: Methods for determining which image of a set of images to present in a search results page for a product are described. Components of a server system may receive a set of images for a set of items associated with a product. Components of the server system may perform image ranking to rank the set of images to identify a representative image of the set of images for the product, based on a user interaction metric of each image of the set of images. The components of the server system may then receive, from a user device, a search query that may be mapped to the product, and the component of the server system may transmit, to the user device, the search results page that includes at least one item of the set of items and the representative image based on the interaction metric of the representative image.

Abstract: A bundle generation engine provides recommendations for an item and at least one compatible item. Upon receiving an item listing for an item at a listing platform, the bundle generation engine determines that unstructured text of an item description for the item listing includes one or more compatible items. For example, the bundle generation engine may use a classification model to determine the unstructured text includes the one or more compatible items. Based on determining that the unstructured text includes the one or more compatible items, the bundle generation engine identifies one or more identifiers within the unstructured text of the item description. For example, the identifiers may be model identifiers or brand identifiers. In aspects, the identifiers are identified using one or more natural language processing models. A bundle recommendation is provided to a user device based on the one or more identifiers.

Abstract: A method of training a machine learning model to promote an item is provided. Acceptance activity of a first entity is monitored and a determination of a first likelihood that the first entity accepts a future offer is made. The acceptance activity and the first likelihood are input as training data for the machine learning model for training purposes. An offer having an acceptance window and a characteristic is received from a second entity for a first item associated with the first entity. A second likelihood that the first entity will accept the offer is determined and an acceptance window is adjusted based on the determination. When the acceptance window closes, the method searches for a second item associated with a third entity based having the characteristic where an offer for the second item is sent to the second entity on behalf of the third entity.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for generating relationship data from listing data. A recommendation system accesses a listing posted to an online marketplace that offers an item for sale. The recommendation system identifies, from listing data included in the listing, a different listing posted to the online marketplace that is offering a recommended item for sale. The listing data is entered by a user that posted the listing to the online marketplace. The recommendation system categorizes the recommended item in a category of items that is related to the item. The recommendation system may generate item recommendation based on the category of items that is related to the item, such as an item recommendation identifying the listing offering the recommended item for sale.

Abstract: Methods for determining which image of a set of images to present in a search results page for a product are described. Components of a server system may receive a set of images for a set of items associated with a product. Components of the server system may perform image ranking to rank the set of images to identify a representative image of the set of images for the product, based on a user interaction metric of each image of the set of images. The components of the server system may then receive, from a user device, a search query that may be mapped to the product, and the component of the server system may transmit, to the user device, the search results page that includes at least one item of the set of items and the representative image based on the interaction metric of the representative image.