In some implementations, a device may receive a document associated with a series of recurring events and associated with an account. The device may analyze, using at least one of an optical character recognition technique or a natural language processing technique, the document to identify one or more characteristics associated with the document. The device may match the document with a record included in a ledger associated with the account based on the one or more characteristics associated with the document, enabling the device to identify that the record is associated with a recurring event of the series of recurring events. The device may modify display information associated with the ledger to append at least one characteristic associated with the document to information associated with the record. The device may transmit, to a user device, the display information to cause the display information to be displayed by the user device.

An example computing system is configured to: (i) access a drawing associated with a construction project; (ii) identify, in the drawing, a set of candidate textual elements that potentially represent a title of the drawing; (iii) for each candidate textual element, (a) determine a respective dataset comprising values for a set of data variables that are potentially predictive of whether the candidate textual element is the title of the drawing, and (b) input the respective dataset into a machine-learning model that functions to (1) evaluate the respective dataset and (2) output, based on the evaluation, a respective score indicating a likelihood that the candidate textual element represents the title of the drawing; and (iv) based on the respective scores for the candidate textual elements that are output by the machine-learning model, select one given candidate textual element as the title of the drawing.

Examples disclosed herein relate to scanning a document comprising a plurality of data elements, mapping, according to a plurality of metadata associated with the scanned document, at least one of the plurality of data elements to a form field according to a trained machine-learning model, and applying the at least one of the plurality of data elements to the form field.

A method and an apparatus for presenting a candidate character string and a method and an apparatus for training a discriminative model are provided. The method for presenting a candidate character string may include: acquiring a character string of alphabetic words inputted by a user; determining a character transition weight of the character string, the character transition weight being used to characterize a transition probability of a character; generating a sort weight corresponding to the character string based on a pre-acquired basic weight matching the character string and the character transition weight; and selecting, according to an order indicated by the sort weight, at least two candidate character strings matching the character string from a pre-acquired candidate character string set for presentation.

Methods and systems for extracting and processing data using optical character recognition in real-time environments. For example, the methods and systems provide novel techniques during extracting data using OCR and for a mechanism to process that data. These methods and systems are particularly relevant in real-time environments as the methods and system limit the need for manual review.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for switching tickets between attendees during an event. The method may include the actions of receiving ticket information from multiple users attending an event, determining that tickets for a particular section are held by one or more of the multiple users, providing a switch offer to the particular user to switch a ticket of the particular user with a ticket held by one of the one or more of the multiple users, receiving a switch request for the switch offer, providing switch offers to each of the one or more of the multiple users, receiving an acceptance of the switch offer from a first user of the one or more of the multiple users, and providing an instruction to cancel the switch offers to other users of one or more of the multiple users.

Computer-implemented methods, computer program products, and computer systems for improving intent determination in a messaging dialog manager system. The computer-implemented method for improving intent determination in a messaging dialog manager system may include one or more processors configured for receiving first agent entry data corresponding to a first agent communicating in a messaging dialog interface, determining that the first agent entry data expects a response that is within a first response domain, determining that a first user entry entered in the messaging dialog interface is not within the first response domain. Further, the computer-implemented may include identifying a second agent configured with a second response domain that includes the first user entry and transmitting the first user entry to the second agent to facilitate a seamless transition of an established communicational flow between the first agent and a first user.

A computer system is provided, comprising a processor; a communications module coupled to the processor; and a memory module coupled to the processor and storing instructions that, when executed by the processor, cause the computer system to: receive an image representing a check; extract data from a portion of the image; identify routing data, based on the extracted data, from a recipient field associated with the check; and initiate an electronic transfer by sending a transfer message using the routing data.

We describe offline links to online digital assets. The offline links can be in hardcopy text. A link can be in a format like [BBQ Ribs], where there is a starting delimiter (eg “[”) and a closing delimiter (“]”). We call this a “linket”. A user has a mobile device with a camera. She scans a linket in hardcopy she is reading. Her device converts this to digital form and sends to a server. The server maps the linket to an URL or other electronic data. The linket acts as a brand, akin to a domain name.

Aspects of the disclosure provide for automatically generating labels for sensor data. For instance, first sensor data for a vehicle may be identified. This first sensor data may have been captured by a first sensor of the vehicle at a first location during a first point in time and may be associated with a first label for an object. Second sensor data for the vehicle may be identified. The second sensor data may have been captured by a second sensor of the vehicle at a second location at a second point in time outside of the first point in time. The second location is different from the first location. A determination may be made as to whether the object is a static object. Based on the determination that the object is a static object, the first label may be used to automatically generate a second label for the second sensor data.