Integration of a computer-based message priority system with mobile electronic devices
First Claim
1. A computer-implemented method comprising:
- generating a priority of received text based on a trainable text classifier that classifies the priority of the received text based at least in part on analyzing the received text and inferred or determined user state;
explicitly training the trainable text classifier to determine the priority of the received text to facilitate generating the priority of the received text, the trainable text classifier is explicitly trained using a set of time-critical texts and a set of non-time-critical texts to facilitate training the trainable text classifier to discriminate between time-critical text and non-time-critical text;
implicitly training the trainable text classifier to determine the priority of the received text and updating the trainable text classifier in real time to continually refine the trainable text classifier to facilitate generating the priority of the received text; and
alerting a user on an electronic device based at least in part on an alert criteria upon determining that the priority of the received text is greater than a predetermined threshold.
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Accused Products
Abstract
Methods for integrating mobile electronic devices with computational methods for assigning priorities to documents are disclosed. In one embodiment, a computer-implemented method first receives a new document such as an electronic mail message. The method assigns a priority to the document, based on a text classifier such as a Bayesian classifier or a support-vector machine classifier. The method then alerts a user on an electronic device, such as a pager or a cellular phone, based on an alert criteria that can be made sensitive to information about the location, inferred task, and focus of attention of the user. Such information can be inferred under uncertainty or can be accessed directly from online information sources. One embodiment makes use of information from an online calendar to control the criteria used to make decisions about relaying information to a mobile device.
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Citations
32 Claims
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1. A computer-implemented method comprising:
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generating a priority of received text based on a trainable text classifier that classifies the priority of the received text based at least in part on analyzing the received text and inferred or determined user state; explicitly training the trainable text classifier to determine the priority of the received text to facilitate generating the priority of the received text, the trainable text classifier is explicitly trained using a set of time-critical texts and a set of non-time-critical texts to facilitate training the trainable text classifier to discriminate between time-critical text and non-time-critical text; implicitly training the trainable text classifier to determine the priority of the received text and updating the trainable text classifier in real time to continually refine the trainable text classifier to facilitate generating the priority of the received text; and alerting a user on an electronic device based at least in part on an alert criteria upon determining that the priority of the received text is greater than a predetermined threshold. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computer-implemented method comprising:
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training a text classifier comprising at least one of a Bayesian classifier or a support-vector machine classifier, or a combination thereof, the training of the text classifier comprising; explicitly training the text classifier to determine a priority of received text to facilitate generating the priority of received text, the text classifier is explicitly trained using a set of time-critical texts and a set of non-time-critical texts to facilitate training the text classifier to discriminate between time-critical text and non-time-critical text, and implicitly training the text classifier to determine the priority of received text based in part on observed user activity with regard to previously received text and updating the text classifier in real time to continually refine the text classifier to facilitate generating the priority of received text; receiving a text comprising an email; generating the priority of the received text based on the text classifier that classifies the priority of the received text based at least in part on analyzing the received text, and inferred or determined user state; and alerting a user on an electronic device based at least in part on an alert criteria, comprising; determining whether the priority of the received text is greater than a predetermined threshold; and alerting the user upon determining that the priority of the received text is greater than the predetermined threshold. - View Dependent Claims (13, 14, 15, 16)
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17. A machine-readable medium having instructions stored thereon for execution by a processor to perform a method comprising:
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explicitly training a text classifier to determine a priority of received text to facilitate generating the priority of the received text, the text classifier is explicitly trained using a set of time-critical texts and a set of non-time-critical texts to facilitate training the text classifier to discriminate between time-critical text and non-time-critical text; implicitly training the text classifier to determine the priority of the received text and updating the text classifier in real time to continually refine the text classifier to facilitate generating the priority of the received text; receiving a text; generating the priority of the received text based on the text classifier that analyzes the received text and a focus of attention of a user; and alerting the user on an electronic device based at least in part on an alert criteria, comprising; determining whether the priority of the received text is greater than a predetermined threshold; and alerting the user upon determining that the priority of the received text is greater than the predetermined threshold. - View Dependent Claims (18, 19, 20, 21, 22, 23)
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24. A computer-implemented system stored on a computer-readable medium comprising:
a trainable text classifier that generates a priority of received text based at least in part on analyzing the received text and user presence information, the trainable text classifier is; explicitly trained to determine the priority of the received text to facilitate generation of the priority of received text, the trainable text classifier is explicitly trained using a set of time-critical texts and a set of non-time-critical texts to facilitate training the trainable text classifier to discriminate between time-critical text and non-time-critical text, and implicitly trained to determine the priority of the received text and updated in real time to continually refine the trainable text classifier to facilitate generation of the priority of the received text; and an alert mechanism that alerts a user on an electronic device based at least in part on an alert criteria that comprises a determination of whether the priority of the received text is greater than a predetermined threshold. - View Dependent Claims (25, 26, 27, 28, 29, 30, 31, 32)
Specification