Method and System for Conversation Detection in Email Systems

• US 20090106375A1
• Filed: 10/23/2007
• Published: 04/23/2009
• Est. Priority Date: 10/23/2007
• Status: Active Grant

• Current Assignee: X Corp. (f/k/a Twitter, Inc.) (X Holdings Corp.)
• Original Assignee: International Business Machines Corporation
• Inventors: Erera, Shai, Carmel, David
• Granted Patent: US 7,693,940 B2
• Time in Patent Office: Days
• US Class Current: 709/206
• CPC Class Codes: G06F 40/194 Calculation of difference between files
• CPC Class Codes: G06F 40/35 Discourse or dialogue representation

Abstract

A method and system are provided for conversation detection in email systems. Multiple email messages are provided and grouped as relating to a conversation. The grouping is carried out by applying a similarity function based on a similarity of the email messages'"'"' attributes, the similarity function including a similarity between the email messages'"'"' participants and at least one of a similarity between the email messages'"'"' subjects or a similarity between the email messages'"'"' contents. The similarity function may also include the similarity between the email messages'"'"' dates. The similarity function may also include weightings for the contributions of the email messages'"'"' attributes. A graphical user interface is provided in an email client which includes means for viewing email messages by conversation.

Claims

1. A method for conversation detection in email systems, comprising:

grouping email messages as relating to a conversation by a similarity function based on a similarity of the email messages'"'"' attributes, the similarity function including;

a similarity between the email messages'"'"' participants; and

at least one of a similarity between the email messages'"'"' subjects or a similarity between the email messages'"'"' contents.

2. The method as claimed in claim 1, wherein the similarity function also includes a similarity between the email messages'"'"' dates.

3. The method as claimed in claim 1, wherein the similarity function includes weightings for the contributions of the email messages'"'"' attributes.

4. The method as claimed in claim 3, wherein the weightings are optimized using machine learning.

5. The method as claimed in claim 1, including:

grouping email messages together in groups having the same core subject;

providing a subject group having the same core subject;

grouping the email messages within a subject group by applying the similarity function; and

defining the resultant groups as sub-conversations.

6. The method as claimed in claim 5, further including:

providing the sub-conversations across all subject groups;

grouping the sub-conversations by applying the similarity function; and

defining the resultant groups as conversations.

7. The method as claimed in claim 5, including sorting the email messages by their date prior to grouping into sub-conversations.

8. The method as claimed in claim 6, including sorting all sub-conversations by their starting date prior to grouping into conversations.

9. The method as claimed in claim 1, including comparing a new message to conversations that previous messages have been grouped into, detecting an optimal conversation for a new message to be added to.

10. The method as claimed in claim 2, including defining a maximum date difference between email messages, above which the date similarity is zeroed.

11. The method as claimed in claim 1, wherein the similarity between the email messages'"'"' participants includes distinguishing between active and passive participants by applying an activity weighting to a participant in an email message.

12. A system for conversation detection in email systems, comprising:

a plurality of email messages each having defined attributes;

means for grouping email messages as relating to a conversation by a similarity function based on a similarity of the email messages'"'"' attributes, the similarity function including;

a similarity between the email messages'"'"' participants; and

at least one of a similarity between the email messages'"'"' subjects or a similarity between the email messages'"'"' contents.

13. The system as claimed in claim 12, wherein the similarity function also includes a similarity between the email messages'"'"' dates.

14. The system as claimed in claim 12, including means to set weightings for the contributions of the email messages'"'"' attributes in the similarity function.

15. The system as claimed in claim 12, including:

means for grouping email messages together in subject groups having the same core subject;

means for grouping the email messages within a subject group by applying the similarity function, and defining the resultant groups as sub-conversations; and

means for grouping the sub-conversations across all subject groups by applying the similarity function, and defining the resultant groups as conversations.

16. The system as claimed in claim 15, including means for comparing a new message to conversations that previous messages have been grouped into, and means for detecting an optimal conversation for a new message to be added to.

17. An email client system for conversation detection, comprising:

a plurality of email messages each having defined attributes;

a graphical user interface for displaying messages, including;

means for displaying email messages grouped as relating to a conversation by a similarity function based on a similarity of the email messages'"'"' attributes, the similarity function including;

a similarity between the email messages'"'"' participants; and

at least one of a similarity between the email messages'"'"' subjects or a similarity between the email messages'"'"' contents.

18. The email client system as claimed in claim 17, including means for adding and removing an email message to a conversation.

19. The email client system as claimed in claim 17, including means to select one of a plurality of conversation choices for a new email messages to be added, the conversation choices being the best similarity matches to the new email message from the conversations of previous email messages.

20. A computer program product stored on a computer readable storage medium for conversation detection in email systems, comprising computer readable program code means for performing the step of:

grouping email messages as relating to a conversation by a similarity function based on a similarity of the email messages'"'"' attributes, the similarity function including;

a similarity between the email messages'"'"' participants; and

at least one of a similarity between the email messages'"'"' subjects or a similarity between the email messages'"'"' contents.