System and Method For Processing Multi-Modal Communication Within A Workgroup

• US 20080189633A1
• Filed: 12/27/2007
• Published: 08/07/2008
• Est. Priority Date: 12/27/2006
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Zhang, Yu, Boyle, Peter Currie
• Granted Patent: US 8,589,778 B2
• Time in Patent Office: Days
• US Class Current: 715/764
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

There is disclosed a system and method for processing multi-modal collaboration. In an embodiment communication received from multiple modes are converted into a common format. Using various conversion modules, the communication may be converted into a common electronic text format (e.g. ASCII text) that contains keywords. Once the communication is converted into a common format, the information contained in the communication may be analyzed and consolidated into related areas or topics. The consolidated information may then be searched for common references in order to augment the information context.

Claims

1. A method of processing multi-modal communications, comprising the steps of:

intercepting each incoming message of a plurality of messages, with the plurality of messages are characterized by at least two different modes;

converting, as necessary, each message into a common text format; and

parsing each message, in the common text format, into a list of keywords.

2. The method of claim 1, further comprising the steps of:

analyzing the list of keywords for each message to generate a respective vector of keywords for each message; and

calculating a similarity distance between the messages based on their respective vectors of keywords.

3. The method of claim 2, further comprising the step of clustering the messages into a plurality of message clusters based upon the calculated similarity distances.

4. The method of claim 3, further comprising the steps of:

searching for common references in the messages of a given message cluster;

obtaining contextual content related in subject matter to the common references;

and linking the related contextual content of the common references to the common references.

5. The method of claim 4, wherein the linking step comprises hyperlinking the related contextual content.

6. The method of claim 4, further comprising the step of displaying the plurality of message clusters as a list of context threads.

7. A system for processing multi-modal communications, comprising:

a real time message monitor component for intercepting each incoming message;

a conversion module for converting, as necessary, each message into a common text format; and

a natural language parsing engine configured to parse each message in the common text format into a list of keywords.

8. The system of claim 7, further comprising a digital hierarchical dictionary for calculating a similarity distance between the list of keywords for each message.

9. The system of claim 8, further comprising a member similarity based clustering algorithm module for clustering the messages into context threads.

10. The system of claim 9, further comprising a context augmenting module configured to search the messages for common references, and to augment the context of the common references by linking related content.

11. The system of claim 10, wherein the context augmenting module is further configured to hyperlink the related content.

12. The system of claim 9, further comprising a GUI component configured to show the clustered messages as a list of context threads.

13. A data processor readable medium storing data processor code that, when loaded into a data processing device, adapts the device to perform a method of processing multi-modal communications, the data processor readable medium comprising:

code for intercepting a plurality of incoming text based messages;

code for converting each incoming text based message into a corresponding common format text message;

code for intercepting a plurality of incoming audio based messages;

code for converting each incoming audio based message into a corresponding common format text message; and

code for parsing each common format text message into a list of keywords.

14. The data processor readable medium of claim 13, further comprising:

code for analyzing the list of keywords for each common format text message to generate a respective vector of keywords for each common format text message; and

code for calculating a similarity distance between the common format text messages based on their respective vectors of keywords.

15. The data processor readable medium of claim 14, further comprising code for clustering into topical message clusters based upon the calculated similarity distances.

16. The data processor readable medium of claim 15, further comprising:

code for searching for common references in the common format text messages of a topical message cluster;

code for obtaining contextual content related in subject matter to the common references; and

code for linking the related contextual content to the common references.

17. The data processor readable medium of claim 16, further comprising code for hyperlinking the related content.

18. The data processor readable medium of claim 15, further comprising code for displaying the clustered messages as a list of context threads.

19. The medium of claim 13 further comprising:

code for intercepting a plurality of incoming audiovisual based messages; and

code for converting an audio portion of each incoming audiovisual based message into a corresponding common format text message.

20. The medium of claim 13 further comprising:

code for intercepting a plurality of incoming image based messages; and

code for converting each image based message into a corresponding common format text message.