SYSTEMS AND METHODS FOR EXCHANGING INFORMATION IN A LARGE GROUP

• US 20100011072A1
• Filed: 06/08/2009
• Published: 01/14/2010
• Est. Priority Date: 07/11/2008
• Status: Active Grant

• Current Assignee: Yuriy Mishchenko
• Original Assignee: Yuriy Mishchenko
• Inventors: Mishchenko, Yuriy
• Granted Patent: US 8,335,827 B2
• Time in Patent Office: Days
• US Class Current: 709/206
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

Systems and methods are disclosed for actively all-to-all exchanging messages in a large group of individuals, comprising accumulating messages from individuals in at least one hub, processing and reorganizing accumulated messages and their groups into short representations of the messages, and selectively actively delivering short representations according to a distribution pattern found as a maximum of a goodness function. Processing and reorganizing accumulated messages into short representations, that is summarization, is performed by constraining the stream of messages to a hierarchical stream format, having a hierarchy of messages linked by a directional parent-child relationship, and iteratively replacing the parent messages in such hierarchy with a representative message chosen among all children of that message. Distribution pattern of the messages containing short representations is found by constrained maximization of a predetermined goodness function depending on the entire distribution pattern jointly for all messages and all users. The process of summarizing messages into short representations, and the process of calculating goodness function for distribution patterns are formulated in terms of statistical model of individuals'"'"' expertise and interests, which is learnt from observing past individuals'"'"' activity.

Claims

1. An electronically implemented method for actively exchanging messages in a group of individuals, comprising:

a. accumulating messages from individuals in at least one hub;

b. processing and reorganizing accumulated messages and their groups into short representations of the messages; and

c. selectively distributing messages containing the short representations according to a distribution pattern achieving a constrained maximum of a goodness function depending on the distribution pattern and parameters describing group members and the messages.

2. The method of claim 1, wherein the goodness function depends jointly on the distribution pattern of all messages and all users.

3. The method of claim 1, wherein processing and reorganizing of accumulated messages is based on a hierarchical conversation format in which a hierarchy of messages comprises a directional parent-child relationship.

4. The method of claim 3, comprising applying a reduction model and a model of individuals'"'"' expertise to generate a short representation of the group of same-parent messages.

5. The method of claim 4, comprising determining the parameters for the model of individuals'"'"' expertise from observations of past individuals'"'"' activity.

6. The method of claim 1, wherein the active communication channel provides online “

live”

conversations between an individual and the group.

7. The method of claim 1, wherein the messages include text messages, voice messages, or video messages.

8. The method of claim 1, wherein the messages are accumulated and distributed by a website, an email, Short Message Service, Instant Messaging, or a mobile communication device.

9. The method of claim 1, comprising actively soliciting feedback from individuals to messages by distributing each message via email, Short Message Service or Instant Messages to a selected number of individuals according to predetermined criteria.

10. The method of claim 1, comprising selecting a distribution pattern of messages to users to maximize the goodness function, which depends on the features of messages and individuals and the set of distribution lists for all members either jointly or separately, and wherein messages are either processed before re-distribution or re-distributed in their original form.

11. A method for distributing messages to individuals in a communication system, comprising

a. accumulating messages from individuals in at least one hub;

and

b. distributing messages to individuals according to one or more distribution lists specifying which messages are to be delivered to each individual, wherein the one or more distribution lists are chosen by finding a maximum of a goodness function.

12. The method of claim 11, wherein the goodness function comprises a function of features describing messages and individuals and the set of all distribution lists for all individuals, simultaneously and jointly, wherein the maximum is subject to a constraint described in terms of features of messages and users and the distribution lists for all individuals jointly or independently.

13. The method of claim 11, comprising generating a model of individuals'"'"' interests, wherein the model is used to determine distribution patterns.

14. The method of claim 11, wherein the goodness function is a sum of predetermined match-scores for assignment pairs, message-to-user, from all distribution lists for all users.

15. The method of claim 13, comprising determining the parameters of the model of individuals'"'"' interests from observations of past individuals'"'"' activity.

16. A method for summarizing a stream of messages, comprising

a. constraining the messages to a hierarchical stream format having a hierarchy of messages linked by a directional parent-child relationship, and

b. summarizing the messages by iteratively replacing each parent message with a replacement message by applying contents reduction to all children of the parent message and the parent message.

17. The method of claim 16, wherein users indicate position of messages within the hierarchical stream format when submitting the messages.

18. The method of claim 16, comprising the replacement message being a single message from the group of all same-parent messages or the parent message.

19. The method of claim 18, wherein a model of individuals'"'"' expertise is used to select the replacement message.

20. The method of claim 19, comprising determining the parameters of the model of individuals'"'"' expertise from observations of past individuals'"'"' activity.