发明申请
US20050021485A1 Continuous time bayesian network models for predicting users' presence, activities, and component usage
有权
连续时间贝叶斯网络模型,用于预测用户的存在,活动和组件使用情况
- 专利标题: Continuous time bayesian network models for predicting users' presence, activities, and component usage
- 专利标题(中): 连续时间贝叶斯网络模型,用于预测用户的存在,活动和组件使用情况
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申请号: US10882068申请日: 2004-06-30
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公开(公告)号: US20050021485A1公开(公告)日: 2005-01-27
- 发明人: Uri Nodelman , Eric Horvitz
- 申请人: Uri Nodelman , Eric Horvitz
- 申请人地址: US WA Redmond
- 专利权人: Microsoft Corporation
- 当前专利权人: Microsoft Corporation
- 当前专利权人地址: US WA Redmond
- 主分类号: G06Q10/10
- IPC分类号: G06Q10/10 ; G06E1/00 ; G05B13/02 ; G06E3/00 ; G06F15/16 ; G06F15/18 ; G06G7/00
摘要:
The present invention relates to a system and methodology to facilitate collaboration and communications between entities such as between automated applications, parties to a communication and/or combinations thereof. The systems and methods of the present invention include a service that supports collaboration and communication by learning predictive continuous time Bayesian models that provide forecasts of one or more aspects of a users' presence and availability. Presence forecasts include a user's current or future locations at different levels of location precision and usage of different devices or applications. Availability assessments include inferences about the cost of interrupting a user in different ways and a user's current or future access to one or more communication channels. The predictive models are constructed from data collected by considering user activity and proximity from multiple devices, in addition to analysis of the content of users' calendars, the time of day, and day of week, for example. Various applications are provided that employ the presence and availability information supplied by the models in order to facilitate collaboration and communications between entities.
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