IT RESOURCE EVENT SITUATION CLASSIFICATION AND SEMANTICS

• US 20090006298A1
• Filed: 09/05/2008
• Published: 01/01/2009
• Est. Priority Date: 04/27/2005
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Minerley, Kevin Gordon, Salahshour, Abdolreza, Sheng, Ma, Loewenstern, David Matthew
• Granted Patent: US 7,730,007 B2
• Time in Patent Office: Days
• US Class Current: 706/46
• CPC Class Codes: G06F 9/542 Event management; Broadcasting; Multicasting; Notifications

Abstract

An off-line knowledge acquisition process takes IT resource messages and automatically generates a set of rules used to provide situation categories for the resource messages/events. The off-line knowledge acquisition process generates an event-to-situation mapping file for efficiently mapping situation to events in runtime. Rules are fed back into a knowledge repository and process for reuse. The off-line knowledge acquisition process provides methods to reiterate the process of mining (autonomically and/or by human interaction) to improve the rules and confidence level assigning the situation categories. A runtime categorizer component uses the event-to-situation mapping file to add situation categories to the IT resource events. The runtime categorizer uses a plurality of annotator components each capable of adding a situation annotation to incoming messages based on rules generated by the off-line knowledge acquisition process. An assessment component chooses the best situation category from those annotated by the annotator components.

Claims

1. A computer program product for classifying a message, the computer program product comprising:

a computer readable medium having computer readable program code embodied therein, the computer readable program code comprising;

computer readable program code configured to receive a message to be classified, said message having a message identifier;

computer readable program code configured to determine if said message identifier uniquely maps to a corresponding classification category;

computer readable program code configured to label the message with the identified classification category if said message identifier maps directly to a corresponding classification category;

computer readable program code configured to parse the message to be classified and identify a plurality of features from the parsed message if said message identifier does not map directly to a corresponding classification category;

computer readable program code configured to compare at least one classification rule to the plurality of features if said message identifier does not map directly to a corresponding classification category;

computer readable program code configured to rate each classification rule that matches to said plurality of features;

computer readable program code configured to identify a classification category from said rating; and

computer readable program code configured to label the message with the identified classification category.

2. The computer program product of claim 1, further comprising:

computer readable program code configured to compare a second classification rule to the plurality of features.

3. The computer program product of claim 1, further comprising:

computer readable program code configured to receive a plurality of messages;

computer readable program code configured to parse the plurality of messages;

computer readable program code configured to identify features from the plurality of messages;

computer readable program code configured to select a common classification category semantic;

computer readable program code configured to match at least some of the identified features with the common classification category semantic; and

computer readable program code configured to generate a classification rule from the identified features matched with the common classification category semantic.

4. The computer program product of claim 1, further comprising:

computer readable program code configured to receive a plurality of messages;

computer readable program code configured to parse the plurality of messages;

computer readable program code configured to identify features from the plurality of messages;

computer readable program code configured to select a plurality of common classification category semantics;

computer readable program code configured to match at least some of the identified features with the respective plurality of common classification category semantics;

computer readable program code configured to identify messages corresponding to the at least some of the identified features; and

computer readable program code configured to generate a classification category to message map.

5. A system for classifying a message, the system comprising:

a module configured to receive a message to be classified, said message having a message identifier;

a module configured to determine if said message identifier uniquely maps to a corresponding classification category;

a module configured to label the message with the identified classification category if said message identifier maps directly to a corresponding classification category;

a module configured to parse the message to be classified and identify a plurality of features from the parsed message if said message identifier does not map directly to a corresponding classification category;

a module configured to compare at least one classification rule to the plurality of features if said message identifier does not map directly to a corresponding classification category;

a module configured to rate each classification rule that matches to the plurality of features;

a module configured to identify a classification category from said rating; and

a module configured to label the message with the identified classification category.

6. The system of claim 5, further comprising:

a module configured to compare a second classification rule to the plurality of features.

7. A method of classifying a message, the method comprising:

receiving a message to be classified on a server, said message having a message identifier;

determining if said message identifier uniquely maps to a corresponding classification category;

labeling the message with the identified classification category if said message identifier maps directly to a corresponding classification category;

parsing the message to be classified and identifying a plurality of features from the parsed message if said message identifier does not map directly to a corresponding classification category;

comparing at least one classification rule to the plurality of features if said message identifier does not map directly to a corresponding classification category;

rating each classification rule that matches to said plurality of features;

identifying a classification category from said rating; and

labeling the message with the identified classification category.

8. The method of claim 7, further comprising:

comparing a second classification rule to the plurality of features.

9. The method of claim 7, further comprising:

receiving a plurality of messages on one or more servers;

parsing the plurality of messages;

identifying features from the plurality of messages;

selecting a common classification category semantic;

matching at least some of the identified features with the common classification category semantic; and

generating a classification rule from the identified features matched with the common classification category semantic.

10. The method of claim 7, further comprising:

receiving a plurality of messages on one or more servers;

parsing the plurality of messages;

identifying features from the plurality of messages;

selecting a plurality of common classification category semantics;

matching at least some of the identified features with the respective plurality of common classification category semantics;

identifying messages corresponding to the at least some of the identified features; and

generating a classification category to message map.

11. The method of claim 10, further comprising:

selecting a plurality common classification category semantics;

identifying at least some of the plurality of messages having features matching the plurality of common classification category semantics;

dividing the identifying at least some of the plurality of messages into respective clusters of messages each having a unique common classification category semantic;

reviewing features from messages in the respective clusters; and

revising the classification rule.