Abstract: Technology for rewarding affiliates is provided. In one example, a method may include determining a physical location of a computing device. A purchase intent from the computing device while at the physical location may be identified. An affiliate associated with the physical location may be rewarded for the purchase intent.

Abstract: Disclosed is a tasking system to assign individuals to tasks. The tasking system targets a user for the task based information in a user profile such as demographics, background and reputation of the user to perform a task. The tasking system predicts if a user will do a given task well based on a user's background, user's skill, and applied predictive algorithms. The tasking system manages the workflow of the task, assesses the probability of the user's answer being accurate, and continuously optimizes assignment and assessment of the task to improve data quality.

Abstract: Disclosed is a system (and process) for determining the accuracy of computerized tasks in a task batch. The system calculates a number of reviews to assess the accuracy of a task based on a source accuracy and a reviewer accuracy. The source accuracy is based factors calculated by a predictive model, the factors including a historical accuracy of an authoring user. The reviewer accuracy is based on a true positive rate and a true negative rate of one or more reviewers of the task batch. The system transmits sourced tasks to a same number of reviewers. The system collects reviews and assesses if the task passes review based on the collected number of reviews.

Abstract: Disclosed are various embodiments for browser-based payment for content. A first request for content is sent to a network content server. A response protocol header is received indicating that a payment is sought for the content in response to the first request. Payment manager code integral to a browser or a browser plug-in is executed in response to receiving the response protocol header. A payment-signifying token is received from a payment provider in response to consummating the payment. A second request for the content is sent to the network content server, where the second request includes a request protocol header specifying the payment-signifying token. The content is received from the network content server in response to the second request.

Abstract: Disclosed are various embodiments for browser-based payment for content. A first request for content is sent to a network content server. A response protocol header is received indicating that a payment is sought for the content in response to the first request. Payment manager code integral to a browser or a browser plug-in is executed in response to receiving the response protocol header. A payment-signifying token is received from a payment provider in response to consummating the payment. A second request for the content is sent to the network content server, where the second request includes a request protocol header specifying the payment-signifying token. The content is received from the network content server in response to the second request.

Abstract: Disclosed are various embodiments for browser-based payment for content. A request for content is obtained from a client. It is determined whether a payment is sought for the content. It is determined whether a payment-signifying token is presented in a request protocol header of the request. A response protocol header indicating that the payment is sought is returned to the client in response to the request when the payment is sought for the content and the payment-signifying token is not presented in the request protocol header. The content is returned to the client in response to the request when the payment is sought for the content and the payment-signifying token is presented in the request protocol header.

Abstract: Disclosed is a configuration for segmenting an image. For each user, the configuration computes an accuracy and contribution score. The configuration determines multiple tasks for segmenting an image. For each task, the configuration assigns a particular user to work on a task based on an accuracy or a contribution score of the particular user, receives an indication of a completed task from the particular user, and assesses an accuracy of the completed task based on the accuracy of the particular user. Responsive to determining all multiple tasks are completed accurately, the configuration combines the completed multiple tasks to form a segmented image.

Abstract: Disclosed is a system (and process) for determining the accuracy of computerized tasks in a task batch. The system calculates a number of reviews to assess the accuracy of a task based on a source accuracy and a reviewer accuracy. The source accuracy is based factors calculated by a predictive model, the factors including a historical accuracy of an authoring user. The reviewer accuracy is based on a true positive rate and a true negative rate of one or more reviewers of the task batch. The system transmits sourced tasks to a same number of reviewers. The system collects reviews and assesses if the task passes review based on the collected number of reviews.

Abstract: Disclosed is a tasking system to assign individuals to tasks. The tasking system targets a user for the task based information in a user profile such as demographics, background and reputation of the user to perform a task. The tasking system predicts if a user will do a given task well based on a user's background, user's skill, and applied predictive algorithms. The tasking system manages the workflow of the task, assesses the probability of the user's answer being accurate, and continuously optimizes assignment and assessment of the task to improve data quality.