Community-based message classification and self-amending system for a messaging system

• US 20040128355A1
• Filed: 12/25/2002
• Published: 07/01/2004
• Est. Priority Date: 12/25/2002
• Status: Abandoned Application

• Current Assignee: Tornado Technologies Co. Ltd.
• Original Assignee: Tornado Technologies Co. Ltd.
• Inventors: Chao, Kuo-Jen, Su, Gen-Hung, Tsai, Tu-Hsin
• Application Number:
  US10/248,184
• Publication Number:
  US 20040128355A1
• Time in Patent Office: Days
• US Class Current: 709/206
• CPC Class Codes: H04L 63/14 for detecting or protecting against malicious traffic

Abstract

A server is provided with a classifier capable of assigning a classification confidence score to a message for at least one category. The server is further provided with a categorization database that contains a category sub-database for each category. The classifier utilizes the category database to assign the classification confidence scores. Clients are provided with forwarding modules that are capable of sending update messages to the server and associating the messages with at least one of the categories in the categorization database and a user profile. Initially, a first message is received at a client. The forwarding module is used to forward the first message to the server, and the first message is associated with a first category. A first category sub-database, which corresponds to the first category, in the categorization database is modified according to the first message and the user profile. When a second message is received at the server, the classifier is utilized to assign a classification confidence score to the second message corresponding to the first category according to the modified first category sub-database. Finally, a filtering technique is applied to the second message according to the classification confidence score.

Claims

1. A method for leveraging user knowledge for categorization of messages in a computer network, the computer network comprising a first computer in networked communications with a plurality of second computers, the method comprising:

providing the first computer with a classifier capable of assigning a classification confidence score to a message for at least a category;

providing the first computer with a categorization database that contains a category sub-database for each category;

wherein the classifier utilizes the category database to assign the classification confidence score;

providing each of the second computers with a forwarding module capable of sending a message from the second computer to the first computer and associating the message with at least one of the categories in the categorization database and associating the message with a user profile;

receiving a first message at any of the second computers;

utilizing the forwarding module at which the first message was received to generate and forward a second message to the first computer, contents of the second message based upon contents of the first message, the second message associated with a first category and a first user profile; and

modifying a first category sub-database in the categorization database according to the contents of the second message and the first user profile, the first category sub-database corresponding to the first category.

2. The method of claim 1 wherein modifying the first category sub-database includes generating a message sample entry in the first category sub-database corresponding to the contents of the second message.

3. The method of claim 1 wherein modifying the first category sub-database includes modifying a count entry of a message sample entry according to the first user profile;

wherein the count entry indicates the number of users that submitted content corresponding to the content of the second message.

4. The method of claim 3 further comprising:

receiving a third message at the first computer; and

utilizing the classifier to obtain a classification confidence score for the third message, the classifier utilizing only sample entries that have an associated count value that reaches a predetermined threshold value to perform the classification analysis.

5. The method of claim 4 further comprising applying a filtering technique to the third message according to the classification confidence score.

6. The method of claim 1 further comprising:

obtaining a confidence score of a message sample entry that corresponds to the contents of the second message;

modifying the confidence score according to the first user profile; and

causing the message sample entry to be an active sample entry according to the modified confidence score and a threshold value.

7. The method of claim 6 further comprising:

receiving a third message at the first computer; and

utilizing the classifier to obtain a classification confidence score for the third message, the classifier utilizing only active sample entries.

8. The method of claim 7 further comprising applying a filtering technique to the third message according to the classification confidence score.

9. The method of claim 1 further comprising:

utilizing the classifier to respectively assign new classification confidence scores to all pending messages on the first computer after the modification of the first category sub-database in the categorization database; and

applying a filtering technique to all of the pending messages according to the respective new classification confidence scores.

10. The method of claim 1 wherein the first computer is a message server and the second computers are client computers of the message server.

11. A computer readable media containing program code for implementing the method of claim 1.

20. The computer network of claim 12 wherein the first computer further comprises:

means for utilizing the classifier to respectively assign new classification confidence scores to all pending messages on the first computer after the modification of the first category sub-database in the categorization database according to the received update message; and

means for applying a filtering technique to all of the pending messages according to the respective new confidence scores.

12. A computer network comprising:

a first computer; and

a plurality of second computers networked to the first computer;

wherein the first computer comprises;

a classifier capable of assigning a classification confidence score to a message for at least a category defined by a categorization database that contains a category sub-database for each category, the classifier capable of utilizing the category database to assign the classification confidence score to the message;

means for receiving an update message associated with a first category from any of the second computers; and

means for modifying a first category sub-database in the categorization database according to the update message and a user profile associated with the update message, the first category sub-database corresponding to the first category; and

the second computers each comprise;

means for receiving a first message; and

means for sending a second message to the first computer and associating the second message with at least one of the categories in the categorization database and a corresponding user profile, contents of the second message based upon contents of the first message.

13. The computer network of claim 12 wherein the means for modifying the first category sub-database is capable of generating a message sample entry in the first category sub-database corresponding to the received update message.

14. The computer network of claim 12 wherein the means for modifying the first category sub-database is capable of modifying a count entry corresponding to the received update message according to the user profile associated with the received update message;

wherein the count entry indicates the number of users that submitted content corresponding to content of the received update message.

15. The computer network of claim 14 wherein the first computer further comprises:

means for receiving a third message from the network; and

means for utilizing the classifier to assign a classification confidence score to the third message;

wherein the classifier utilizes only sample entries that have an associated count value that reaches a predetermined threshold value to perform the classification analysis.

16. The computer network of claim 15 wherein the first computer further comprises means for applying a filtering technique to the third message according to the classification confidence score.

17. The computer network of claim 12 wherein the first computer further comprises:

means for obtaining a confidence score of a message sample entry that corresponds to the received update message;

means for modifying the confidence score according to the user profile associated with the received update message; and

means for causing the message sample entry to be an active sample entry according to the modified confidence score and a threshold value.

18. The computer network of claim 17 wherein the first computer further comprises:

means for receiving a third message from the network; and

means for utilizing the classifier to obtain a classification confidence score for the third message, the classifier utilizing only active sample entries.

19. The computer network of claim 18 wherein the first computer further comprises means for applying a filtering technique to the third message according to the classification confidence score.

21. The computer network of claim 12 wherein the first computer is a message server and the second computers are client computers of the message server.