T-mobile Usa, Inc.

Paypal, Inc.

Uber Technologies, Inc.

Oracle International Corporation

Parker Ralph Kuncl

Daniel Brain

Miriam Ferhut

Anurag Sinha

Awaneesh Verma

Sinclair M Temple

Ashley Quitoriano

Prarthana H Panchal

Winston Wang

Mark Drovdahl

Paulo Chow

Kelly Bailey

Matthew Brigante

Michael Kemery

Jonathan Lawrence Mann

Richard Alan Ewing, Jr

Nenad Nestorovic

Joshua J Hinds

Youjin Nam

Gabriel Alexander Biller

Jedediah Joaquin McCann

Adam Jeremy Share

Benoit F Collette

Tadeo T Toulis

Eric Mai

Richard Alan Ewing

Techniques for real-time expense auditing and machine learning are disclosed. An expense auditing system trains a machine learning model to compute audit risk scores as a function of expense descriptions. The auditing system receives an expense description associated with an employee. The expense auditing system computes, using the trained machine learning model, an audit risk score associated with the expense description. The expense auditing system compares the audit risk score with an audit trigger. The audit trigger includes one or more conditions that, when satisfied, identifies expense descriptions that are at risk of being audited. The expense auditing system determines that the audit risk score satisfies the audit trigger. Responsive to determining that the audit risk score satisfies the audit trigger, the expense auditing system alerts the employee that the expense description is at risk of being audited.

Real-time expense auditing and machine learning system

A network system facilitates management of the operational states of transportation vehicles. Within a system environment, the network system also coordinates transport service between service providers operating the transportation vehicles and service requestors operating client devices. A transportation vehicle includes a processor or computing device that can determine and change operational states of the transportation vehicle. The transportation vehicle communicates operational states to one or more devices in the environment. Operational states can be communicated as vehicle datasets using a communication port of the transportation vehicle. The network system and client devices can act to enhance transport service using vehicle datasets. For example, the network system and/or client devices can manage an operational state by changing the current operational state off the transportation vehicle to a different operational state. Transport service can be enhanced at various points during the transport service coordination.

Managing the operational state of a vehicle

The systems and methods that generate a one-touch frame are provided. A line of code including a tag is inserted into a webpage. The tag includes a link to a server from which parameters for the frame are obtained. The browser uses the parameters to generate the frame, In addition, the server or a local memory of a computing device on which the frame is generated also store credentials associated with a user account. These credentials are also obtained and incorporated into the frame. The frame may then be activated to perform one-touch functions using the credentials.

One line in-context user interface

A computer system operates to receive transport service requests from computing devices of requesters within a geographic region. The system matches each transport service request with an available transport provider operating a service vehicle within the geographic region, and determines a location bias for a first transport provider that operates a corresponding vehicle within the geographic region, the location bias being associated with a preferred location of the first transport provider. The system may then match the first transport provider to a transport service request based on (i) the location bias of the first transport provider, and (ii) a destination of the transport service request which, upon fulfilling the transport service request, results in the first transport provider being positioned to arrive at the preferred location within a future time interval.

Network computer system to position transport providers using provisioning level determinations

The systems and methods that generate a one-touch frame are provided. A line of code including a tag is inserted into a webpage. The tag includes a link to a server from which parameters for the frame are obtained. The browser uses the parameters to generate the frame. In addition, the server or a local memory of a computing device on which the frame is generated also store credentials associated with a user account. These credentials are also obtained and incorporated into the frame. The frame may then be activated to perform one-touch functions using the credentials.

Techniques for expense report submission are disclosed. An expense report submission system receives, via a graphical user interface, a user query that corresponds to requesting whether a particular expense is allowed. The expense report submission system applies the user query to a machine learning model configured to evaluate data associated with expenses against one or more expense policy rules. The expense report submission system generates a response to the user query based at least on a result of applying the user query to the machine learning model. The response to the user query indicates whether the expense is allowed based at least on the expense reporting rule(s). The expense report submission system presents, in the graphical user interface, the response to the user query.

Expense report submission interface

A network computer system operates to estimate a quantity of service vehicles operating in a geographic region during a future time interval. For the future time interval, the network computer system determines a current forecast of a provisioning level for a service provided by the projected quantity of service vehicles in each of multiple subregions of the geographic region. The network computer system also determines a location bias for one or more service providers, each operating a corresponding vehicle within the given geographic region. Additionally, the network computer system matches each service provider to a service request based on (i) the location bias of the service provider, (ii) a service location of the service request, and (iii) a determination as to an effect of matching the service provider on the current forecast for the provisioning level.

Network computer system to position service providers using provisioning level determinations

A telecommunication device configured to perform at least one of adjusting a network polling frequency, prompting a user to select one of a plurality of networks, automatically connecting to one of the networks, or automatically disconnecting from one of the networks is described herein. The telecommunication device performs the adjusting, prompting, or connecting based at least on received device data or network data that is associated with the networks.

Smart connection manager

A user interface presents a plurality of items configured as a stack in a display of a device. The stack is scrollable in a direction oblique to a plane of the display for successively viewing the items in the stack. Some implementations provide for control of the user interface based on input from a finger position sensor or a slider.

User interface with z-axis interaction

Growing community of inventors

Seattle, WA, United States of America

Parker Ralph Kuncl