A method comprising navigating to a first investment interface publishing a first particular loan opportunity among different loan opportunities, the loan opportunity being based on first loan terms and first property information, receiving different loan opportunities based on the first query, providing a selection of the first particular loan opportunity, receiving details of the first particular loan opportunity, providing a first commitment from the first investor system to partially fund a first partial funding of a loan amount associated with the first particular loan opportunity, a second commitment from the second investor system being already provided to the investment system to partially fund a second partial funding, receiving an indication that a first loan is to be provided to the first property owner when the loan amount is completely funded, and receiving distributions, every day, of daily returns by the first investor.

An information processing apparatus 10 acquires face image data of a passenger 55 who has disembarked from an aircraft, and acquires flight information corresponding to the face image data acquired by an image capture device 51 from a storage device 52 in which flight information of the passenger 55 and the face image data of the passenger 55 are stored in association with each other in advance. It is determined based on the acquired flight information whether the passenger 55 is a transit passenger. Sightseeing area information regarding the sightseeing area of the tour is acquired, and if the passenger is a transit passenger, a tour based on the sightseeing area information and flight information is searched for. The information of the searched-for tour is displayed on display devices 53 and 54.

An online concierge system maintains information about items offered for purchase and users of the online concierge system. Based on prior purchases of items by users, the online concierge system trains a model to determine a likelihood of a user purchasing an item based on an embedding for the object and embedding for the user. The online concierge system identifies a collection of items and generates an embedding for the collection. The collection may be a cluster of items determined from similarities between embeddings of items. Alternatively, the collection may be a group of items having a common category. The online concierge system includes one or more collections of items along with individual items when recommending items for the users, so the trained model is applied to embeddings of the individual items and to embeddings of the one or more collections to generate recommendations for a user.

An online concierge system generates an item graph connecting item nodes with attribute nodes of the items. Example attributes include a brand, a category, a department, or any other suitable information about the item. When the online concierge system receives a search query to identify one or more items from a customer, the online concierge system parses the search query into combinations of terms and identifies item nodes and attribute nodes related to the search query. The online concierge system identifies item nodes and attribute nodes that are likely to result in a conversion. Information about the identified nodes is presented to the customer. The customer may select an item node to purchase the item, or an attribute node to execute a new search query based on terms associated with the attribute node.

A system and method for providing payments is disclosed. A method can include establishing a wireless link between a mobile device and a merchant device. After an instruction is displayed on the mobile device, a combination of a first type of input and a second type of input are received on the mobile device, first type of input including at least one button press of a physical button and the second type of input received from a user to confirm a payment for the purchase. Based on the inputs, payment data is retrieved from a memory of the mobile device. The method includes receiving the payment data at the merchant device to make the purchase, wherein receiving the payment data, via the wireless link, at the merchant device to make the purchase is performed according to a protocol for communicating the payment data to the merchant device.

A method includes receiving data characterizing a query for information associated with a first item of a plurality of items in an item catalog. The method also includes determining an attribute of the first item. The determining can be performed using a predictive model trained using question-answer pair data associated with a portion of the plurality of items. The portion can include a second item. The method can further include determining an attribute value of the attribute using a mapping of attributes and attribute values associated with the plurality of items in the item catalog. The method can also include providing, as an answer to the query, a characterization of the attribute value. Related systems, methods, apparatus, and computer readable mediums are also described.

Methods, systems, and storage media for determining the inherent quality of seats within an event venue and for determining the value of prices of tickets for seats within an event venue are disclosed. Exemplary implementations may: utilize data related to past transactions for tickets and event venue information (e.g., locations of zones, sections, rows, and the like) to train a machine-learning model to determine a seat desirability score for seats in an event venue; determine the best quality seats that are available for future events at the event venue using the seat desirability score; determine a pricing value for tickets in the event venue using the seat desirability score and a ticket price associated with available ticket listings, and display one of one or more seats with the strongest seat desirability score and/or having the strongest pricing value for a ticket-requesting buyer.

A web-based item listing platform provides item listings that users can create or search. Item listings can be generated using structured information extracted while capturing an item listing video of the item. During creation of the item listing video, input prompts are provided to the user that cause a mobile device to provide an input request, such as taking an image of a specific feature of the item or providing some other item description information. During the item listing video, image recognition models may also be employed to determine other item description information, such as the color, the brand, and the like. The item listing can be generated from the item listing video by populating a set of structured data elements associated with an item description type. Each structured data element is populated with the item description information corresponding to the associated item description type.

A computer system for enhanced personal property replacement may be provided. The computer system may include at least one processor in communication with at least one memory device. The at least one processor may programmed to receive a plurality of user preferences transmitted from a user computer device associated with a user, receive a request from the user to cover a claim, determine a first plurality of items for the user based upon the claim and the plurality of user preferences, and/or transmit, to a retailer computer device associated with a retailer, an order for the determined first plurality of items with the retailer to be delivered to the user at an address associated with the user.

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.