Browse Prior Art Database

Method for Relevent Collaborative Business Interaction Disclosure Number: IPCOM000198569D
Publication Date: 2010-Aug-09
Document File: 6 page(s) / 60K

Publishing Venue

The Prior Art Database


Disclosed is a system and method for tagging the content of text-based chat messages in order to optimize discussions and improve business collaboration and productivity.

This text was extracted from a PDF file.
At least one non-text object (such as an image or picture) has been suppressed.
This is the abbreviated version, containing approximately 53% of the total text.

Page 1 of 6

Method for Relevent Collaborative Business Interaction

With an increase in the flow of information and discussions over real-time, direct

text-based platforms such as Instant Messaging (IM), users need to:

Systematically manage chat messages

Improve productivity
Implement and follow-up on decisions
Intelligently use discussions to prevent a re-discussion of the same topic, or make

    further discussions on the same topic more focused and successful
Current IM platforms provide the ability to store a chat history or a record of all client

transcripts during a particular chat session locally; however, no optimizations exist for

loading and delivering these transcripts to the end user for the purpose of improving

business results.

The solution is a tagging system which optimizes IM platforms to improve business

results by performing the following tasks:

The system tags all the chat transcripts with primary keys based on the

discussion topic. If this tag appears in the subject line when a user schedules a

meeting, then the system automatically selects the related chat transcripts and

attaches them to the meeting invitation. [Figure 1] This allows all invitees to be

equipped with the same and most current information.

The system breaks the chat transcript into sections and sets permissions on

particular sections, enabling only a particular subset of the invitee list to view that

section of the transcript. [Figure 2] This way, some of the discussions can be

shared among two parties while some of it can be kept hidden from another


Example: Consider the following group chat from a company A regarding the

collaboration meeting with company B.

A1: The following are the topics we need to discuss with the delegates from

company B…

  A2: We have the following priorities for these topics…

A2: But we do not have a NDA in place. We should not disclose this particular


A1: I agree. This is confidential and very important information. We should not


Page 2 of 6

discuss this with delegates from Company B.

In this case, Section 1 is publicly viewable to delegates from both companies A as

well as B. However, Section 2 is only visible to invitees from company A and to

the ones from company B.

The system analyzes the chat transcripts and, at specific intervals, summarizes

parts of a discussion. When the length of chat exceeds a designated threshold,

this helps users to more quickly review past chats and obtain an overview. Example:
A: I liked your new idea, but what about the prior art
B: This is not applicable here due to...

S: How about this one...

A: Yeah you are right, the prior art is not applicable and hence this should be


S: I agree

In this sample conversation, the system summarizes the discussion that "the idea

being discussed should be submitted as a disclosure." If the participants schedule

a meeting to write the disclosure, this chat discussion along with the summary is

attached to the invite, allowing all participant...