Optimizing performance based on behavioral and situational signals

A technology to optimize performance, signal, applied in the direction of instrumentation, data processing applications, error detection/correction, etc., can solve the resources and knowledge of services and applications that consume computing resources, lack of monitoring and maintenance, management services and Problems such as difficulty in applying computing resources

Active Publication Date: 2019-04-16
MICROSOFT TECH LICENSING LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As the variety and depth of services offered increases, managing the computing resources consumed by services and applications can be difficult for some customers
Business entities often have dedicated professionals, but individuals or small businesses may lack the resources and knowledge to monitor and maintain services and applications that unnecessarily consume computing resources

Method used

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  • Optimizing performance based on behavioral and situational signals
  • Optimizing performance based on behavioral and situational signals
  • Optimizing performance based on behavioral and situational signals

Examples

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Embodiment Construction

[0013] As briefly described above, productivity services can optimize performance based on behavioral and contextual signals. In an example scenario, a productivity service may receive behavioral and / or contextual signals associated with a user. Behavioral signals may include captured user interactions with an application. Furthermore, behavioral signals can encapsulate the timing and frequency of user interactions. Additionally, contextual signals may include the user's location. Behavioral and contextual signals may be captured during periods of expected activity with the user.

[0014] Behavioral signals and / or context signals can be analyzed to infer usage patterns associated with components of the application. A usage pattern can describe the timing of activities associated with a component and the frequency of activities. Next, failures in usage patterns can be detected in comparison to utility thresholds. A utility threshold may include a value for comparing usage ...

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PUM

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Abstract

Variety of approaches to optimize performance based on behavioral and situational signals are described. A productivity service initiates operations to optimize performance upon receiving a behavioralsignal and/or a situational signal associated with a user. The behavioral signal and/or the situational signal are analyzed to infer a usage pattern associated with a component of an application. Next, a failure of the usage pattern is detected in a comparison to a utility threshold. In response, the application is instructed to interrupt an execution of the component.

Description

Background technique [0001] Information exchange changes processes related to work and personal environments. Automation and improvement in the process expands the range of capabilities offered for personal and business consumption. With the development of faster and smaller electronics, the execution of large-scale processes in cloud systems becomes feasible. In fact, applications delivered by data centers, data warehouses, and data workstations have become common features in modern personal and work environments. Such systems execute a wide variety of applications ranging from enterprise resource management applications to off-the-shelf productivity applications. [0002] Online services and applications increasingly provide useful tools for a variety of customers ranging from large corporate entities to small businesses to individuals. As the variety and depth of services offered increases, managing the computing resources consumed by the services and applications can be...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06
CPCG06Q10/06315G06F2201/81G06F11/3438G06F11/302G06F2201/865G06F11/3409G06F11/3466G06F11/30H04L67/535H04L41/147H04L43/16
Inventor Z·H·阿里S·R·曼达章涛S·K·巴拉甘C·皮克洛R·L·小辛普森S·纳利亚E·D·梅洛D·P·里芒特K·C·克莱蒙特T·W·米利特S·卡尔皮内蒂胡晓M·S·雷D·L·迈耶斯
Owner MICROSOFT TECH LICENSING LLC
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