Electrical computers and digital processing systems: multicomput – Computer conferencing – Demand based messaging
Reexamination Certificate
1999-07-30
2003-09-16
Dinh, Dung C. (Department: 2172)
Electrical computers and digital processing systems: multicomput
Computer conferencing
Demand based messaging
C709S207000
Reexamination Certificate
active
06622160
ABSTRACT:
RELATED APPLICATIONS
This application is related to the cofiled, copending and coassigned applications entitled “Methods for Automatically Assigning Priorities to Documents and Messages”, “Integration of a Computer-Based Message Priority System with Mobile Electronic Devices”, “Methods for Display, Notification, and Interaction with Prioritized Messages”, and “A Computational Architecture for Managing the Transmittal and Rendering of Information, Alerts, and Notifications”.
FIELD OF THE INVENTION
This invention relates generally to prioritized text such as prioritized email messages, and more particularly to the routing of such prioritized text.
BACKGROUND OF THE INVENTION
Electronic mail programs have become a popular application among computer users. Especially with the advent of the Internet, exchanging email has almost become a reason why people purchase computers for personal reasons, and within many corporate environments, email has become the standard manner by which coworkers exchange information. However, with the increasing popularity of email, shortcomings have become apparent.
Chief among these shortcomings is that many users now face a deluge of email every day, such that the capability of being able to send and receive email has almost become a hindrance to their day-to-day ability to get their job done, as opposed to being an asset. Some users report receiving over 100 email messages a day. With such large numbers of email, it is difficult to manage the email, such that the users read the most important messages first.
Limited solutions to this problem have been attempted in the prior art. Prior art exists for attempting to curtail the amount of junk email—e.g., unsolicited email, typically regarding a service or product for sale—that users receive. Moreover, some electronic mail programs allow for the generation of rules that govern how an email is managed within the program—for example, placing all emails from certain coworkers in a special folder.
These limited solutions, however, do not strike at the basic problem behind email—that with so much email being received, it would be most useful for a user to be able to have his or her computer automatically prioritize the email by importance or review urgency, and perform actions based on that prioritization. For these and other reasons, there is a need for the present invention.
SUMMARY OF THE INVENTION
The invention relates to the routing of prioritized text such as email messages. In one embodiment, a computer-implemented method first receives a text. The method generates a priority of the text, based on a text classifier such as a Bayesian classifier or a support-vector machine classifier. The method then routes the text based on a routing criteria.
Embodiments of the invention provide for advantages over the prior art. A user, for example, in one embodiment, may ask that he or she only be disturbed if the priority of the text is greater than a given threshold. Thus, even if the user receives over 100 different email, he or she will be alerted to the most important email, and then will be able to deal with the other email when the user has time. Prioritization, in other words, makes email much more useful in environments where a lot of email is exchanged on a regular basis.
REFERENCES:
patent: 5634084 (1997-05-01), Malsheen et al.
patent: 5864848 (1999-01-01), Horvitz
patent: 5907839 (1999-05-01), Roth
patent: 5950187 (1999-09-01), Tsuda
patent: 6021403 (2000-02-01), Horvitz
patent: 6182059 (2001-01-01), Angotti et al.
patent: 6192360 (2001-02-01), Dumais et al.
patent: 6327581 (2001-12-01), Platt
patent: 6411930 (2002-06-01), Burges
patent: 2002/0002450 (2002-01-01), Nunberg et al.
U.S. patent application Ser. No. 09/007,894, Horvitz, filed Jan. 15, 1998.
U.S. patent application Ser. No. 09/055,477, filed Apr. 6, 1998.
M. Sahami, S. Dumais, D. Heckerman, E. Horvitz (1998). A Bayesian approach to filtering junk e-mail. In Workshop on Learning for Text Categorization, AAAI Technical Report WS-98-05. American Association for Artificial Intelligence, AAAI.
J. Breese, D. Heckerman, & C. Kadie (1998). Empirical Analysis of Predictive Algoirthms for Collaborative Filtering. In Proceedings of the Fourteenth Conference on Uncertinaty in Artificial Intelligence, pp. 43-52. AUAI, Morgan Kaufmann, San Francisco.
M. Czerwinski, S. Dumais, G. Robertson, et al. (1999). Visualizing implicit queries for information management and retrieval. In Proceedings of CHI '99, ACM SIGCHI Conference on Human Factors in Computing Systems, Pittsburgh, PA, pp. 560-567. Association for Computing Machinery.
S. Dumais, J. Platt, D. Heckerman, M. Sahami (1998). Inductive learning algorithms and representations for text categorization. In Proceedings of the Seventh International Conference on Information and Knowledge Management, pp. 148-155. Association for Computing Machinery, ACM Press, New York.
E. Horvitz (1999). Principles of mixed-initiative user interfaces. In Proceedings of CHI '99, ACM SIGCHI Conference on Human Factors in Computing Systems, Pittsburgh, PA, pp. 159-166. Association for Computing Machinery.
E. Horvitz, M. Barry (1995). Display of information for time-critical decision making. In Proceedings of the Eleventh Conference on Uncertinaty in Artificial Intelligence, pp. 296-305 Montreal, Canada. Morgan Kaufmann, San Francisco.
E. Horvitz, J. Breese, D. Heckerman, D. Hovel, K. Rommelse (1998). The Lumiere project: Bayesian user modeling for inferring the goals and needs of software users. In Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, pp. 256-265. Morgan Kaufmann, San Francisco.
E. Horvitz and G. Rutledge (1991). Time-dependent utility and action under uncertainty. In Proceedings of Seventh Conference on Uncertainty in Artificial Intelligence, Los Angeles, CA, pp. 151-158. Morgan Kaufmann, San Francisco.
E. Horvitz and A. Seiver (1997). Time-critical action: Representations and application. In Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (UAI-97), pp. 250-257 Providence, RI. Morgan Kaufmann, San Francisco.
D. Koller, M. Sahami (1996). Toward optimal feature selection. In Proceedings of Thirteenth Conference on Machine Learning, pp. 284-292, Morgan Kaufmann, San Francisco.
H. Leiberman (1995). An agent that assist web browsing. In Proceedings of IJCAI-95, Montreal Canada. Morgan Kaufmann, San Francisco.
J. Platt (1999). Fast training of support vector machines using sequential minimal optimzation. In Advances in Kernal Methods: Support Vector Learning. MIT Press, Cambridge, MA.
J. Platt (1999). Proobabilistic outputs for support vector machines and comparison to regularized likelihood methods. In Advances in Large Margin Classifiers, MIT Press, Cambridge, MA.
Dinh Dung C.
Microsoft Corporation
Woo Isaac
LandOfFree
Methods for routing items for communications based on a... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Methods for routing items for communications based on a..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Methods for routing items for communications based on a... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3093858