Method and apparatus for sociological data mining

• US 7,143,091 B2
• Filed: 02/04/2003
• Issued: 11/28/2006
• Est. Priority Date: 02/04/2002
• Status: Expired due to Term

• Current Assignee: Adobe Inc.
• Original Assignee: Cataphorn Incorporated
• Inventors: Charnock, Elizabeth, Roberts, Steven L., Holsinger, David J.
• Primary Examiner(s): Robinson, Greta
• Assistant Examiner(s): LEWIS, CHERYL RENEA
• Application Number:
  US10/358,759
• Publication Number:
  US 20030182310A1
• Time in Patent Office: 1,393 Days
• Field of Search: 707 2- 5, 707/100, 715/500, 715/501.1, 715513-516
• US Class Current: 1/1
• CPC Class Codes: G06F 16/34 Browsing; Visualisation therefor
• CPC Class Codes: G06F 16/38 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access

Abstract

A processing system for retrieving interrelated documents is described. The system comprises a document repository for storing a plurality of documents, a metadata repository for storing a plurality of metadata elements to represent relations between the documents, and a sociological analysis engine to identify relationships between the documents using the metadata elements from the metadata repository.

Claims

1. A computer processing system for retrieving interrelated documents, comprising:

a document repository for storing a plurality of documents, wherein a document is any data that has an inferable or explicit actor and date;

a metadata repository for storing a plurality of metadata elements to represent relations between the documents;

a sociological analysis engine to identify causal relationships between the documents using the metadata elements from the metadata repository.

2. The processing system of claim 1, wherein the sociological analysis engine automatically resolves references to an actor who has more than one electronic identity.

3. The processing system recited in claim 1, wherein the sociological analysis engine automatically resolves reference to an actor who has more than one electronic personality.

4. The processing system recited in claim 1, wherein the sociological analysis engine detects missing data by reference to other documents within the document repository.

5. The processing system recited in claim 1, wherein the sociological analysis engine removes or otherwise makes unavailable documents or parts thereof deemed by the engine to be of a particular content type.

6. The processing system recited in claim 1, wherein the sociological analysis engine categorizes a plurality of documents by iteratively attempting to match the documents to multiple ontology classes, both individually and in combination.

7. The processing system recited in claim 1, wherein the sociological analysis engine determines the most likely correct term in a document that has been input using a process that is subject to error.

8. A computer implemented method for identifying whether a plurality of documents are causally interrelated, the method comprising:

extracting metadata and content from the documents and storing it in a repository, wherein a document is any data that has an inferable or explicit actor and date;

computing metadata for representing a sociological analysis to identify causal interrelations between the documents and storing the metadata in the repository;

and in response to a search query, identifying a plurality of relevant, causally interrelated documents stored in the repository.

9. The method as recited in claim 8, wherein the sociological analysis engine automatically resolves reference to an actor who have more than one electronic identity.

10. The method of claim 8, further comprising:

enabling a user to query based on record type, wherein record type includes one or more of the following;

anomalies, circles of trust, ad hoc workflows, and cliques.

11. A computer implemented method for identifying causal relationships between a plurality of documents comprising:

extracting metadata and content from the documents and storing it in a repository, wherein a document is any data that has an inferable or explicit actor and date;

computing metadata for representing a sociological analysis to identify causal interrelations between the documents and storing the metadata in the repository; and

creating links between the causally related documents.

12. The method of claim 11, further comprising:

identifying patterns in behavior; and

tagging changes in the patterns of behavior over time.

13. The method of claim 12, further comprising:

identifying ad hoc workflows illustrating a directed graph of communication between actors based on the detected patterns of behavior.

14. The method of claim 12, further comprising:

identifying closed loops defining circles of trust based on the detected patterns of behavior over time.

15. The method of claim 11, further comprising:

identifying an actor, wherein the actor may have a plurality of different aliases, and wherein the aliases of the actor may change over time.

16. The method of claim 15, further comprising:

building a behavioral model of the actor, the behavioral model generating an actor heartbeat defining the actor'"'"'s expected behavior.

17. The method of claim 15, further comprising:

identifying the actor'"'"'s importance globally and at a per-conversation level.

18. The method of claim 15, further comprising:

identifying a conversation and identifying each of the actors associated with the conversation.

19. The method of claim 18, further comprising:

categorizing each of the actors in the conversation based on a level of participation.

20. The method of claim 11, further comprising generating a communication graph to determine communication links between the actors.

21. The method of claim 11, further comprising:

in a discussion including quoted text, identifying each text block and attributing the text block to an actor.

22. The method of claim 21, further comprising identifying an arc of discussion and determining pivotal items in the discussion.

23. The method of claim 22, further comprising summarizing the discussion.

24. The method of claim 22, further comprising identifying a resolution of the discussion, if the resolution was reached.

25. The method of claim 24, further comprising identifying a discussion as pending, if the data is real-time data, and no resolution has been reached in the discussion.

26. The method of claim 11, further comprising performing pragmatic tagging on a document to establish intent.

27. The method of claim 11, further comprising:

for each document, determining if the document is an original document or a revised document, and for each revised document, determining a version and history.

28. The method of claim 11, further comprising:

enabling a user to enter a query based on a plurality of questions targeted at one or more actors, and responding to the query with documents which provide yes/no answers to those questions.

29. The method of claim 11, further comprising distinguishing between template based and boilerplate based documents.

30. The method of claim 11, further comprising enabling a user to submit a query by example, based on a submitted discussion or document.