Techniques for creating computer generated notes

• US 8,024,653 B2
• Filed: 06/12/2007
• Issued: 09/20/2011
• Est. Priority Date: 11/14/2005
• Status: Active Grant

• Current Assignee: Make Sence Incorporated
• Original Assignee: Make Sence Incorporated
• Inventors: Bobick, Mark, Wimmer, Carl
• Primary Examiner(s): Hong; Stephen S.
• Assistant Examiner(s): Vaughn; Gregory J
• Application Number:
  US11/761,839
• Publication Number:
  US 20080021701A1
• Time in Patent Office: 1,561 Days
• Field of Search: 715/200, 715/230, 715/231, 715/255, 715/256, 715/259
• US Class Current: 715/231
• CPC Class Codes: G06F 16/258 Data format conversion from or to a database
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/955 using information identifiers, e.g. uniform resource locators [URL]
• CPC Class Codes: G06F 40/20 Natural language analysis semantic analysis of natural language G06F40/30
• CPC Class Codes: G06F 40/247 Thesauruses; Synonyms
• CPC Class Codes: G06F 40/258 Heading extraction; Automatic titling; Numbering
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition

Abstract

Text is extracted from and information resource such as documents, emails, relational database tables and other digitized information sources. The extracted text is processed using a decomposition function to create. Nodes are a particular data structure that stores elemental units of information. The nodes can convey meaning because they relate a subject term or phrase to an attribute term or phrase. Removed from the node data structure, the node contents are or can become a text fragment which conveys meaning, i.e., a note. The notes generated from each digital resource are associated with the digital resource from which they are captured. The notes are then stored, organized and presented in several ways which facilitate knowledge acquisition and utilization by a user.

Claims

1. A method for generating notes comprising:

decomposing resources into a plurality of nodes using natural language parsing to perform word classification based upon parts of speech and so that each node comprises a data structure sufficient to independently convey meaning and including a subject, an attribute, and a bond therebetween;

storing the plurality of nodes in a node pool;

constructing and storing correlations of linked together nodes of the node pool representing knowledge by at least iteratively adding nodes from the node pool onto an end of a chain of nodes by searching the node pool for a match between an attribute of a chained node and a subject of another unchained node in the node pool;

converting the subject, the attribute, and the bond of each node in the node pool into textual objects;

organizing the textual objects from a respective node into a textual phrase to define a note; and

associating notes from each resource into a corresponding note set.

2. The method of claim 1 wherein the organizing comprises associating the subject of the respective node as a note text subject.

3. The method of claim 1 wherein the organizing comprises associating the bond of the respective node as a note text verb.

4. The method of claim 1 wherein the organizing comprises associating the attribute of the respective node as a note text object.

5. The method of claim 1 further comprising eliminating members from the node pool using post generation node filters.

6. The method of claim 1 wherein each node further comprises at least one of a source entry and a sequence entry.

7. The method of claim 1 wherein the node pool permits selection and retrieval using a hash map.

8. The method of claim 1 wherein the nodes are added to the chain of nodes until at least one of the following occurs:

a user halts correlation;

a set time expires;

the chain of nodes comprises a number of nodes greater than a specified number;

no further nodes in the node pool can be associated with the chain of nodes;

a pre-selected term from a target node is added to the correlation; and

a pre-selected target node is added to the correlation.

9. The method of claim 1 further comprising displaying notes defined from the node pool.

10. A method for generating notes comprising:

decomposing resources into a plurality of nodes by using an intermediate format wherein a first term is paired with a second term based upon a relation defined by a context so that each node comprises a data structure sufficient to independently convey meaning and including a subject, an attribute, and a bond therebetween, the context comprising at least one of a schema, a tree graph and a directed graph;

storing the plurality of nodes in a node pool;

constructing and storing correlations of linked together nodes of the node pool representing knowledge by at least iteratively adding nodes from the node pool onto an end of a chain of nodes by searching the node pool for a match between an attribute of a chained node and a subject of another unchained node in the node pool;

converting the subject, the attribute, and the bond of each node in the node pool into textual objects;

organizing the textual objects from a respective node into a textual phrase to define a note; and

associating notes from each resource into a corresponding note set.

11. The method of claim 10 wherein the organizing comprises associating the subject of the respective node as a note text subject.

12. The method of claim 10 wherein the organizing comprises associating the bond of the respective node as a note text verb.

13. The method of claim 10 wherein the organizing comprises associating the attribute of the respective node as a note text object.

14. An apparatus for identifying knowledge comprising:

an input device for permitting input; and

a processor and memory associated therewith and coupled to said input device for

decomposing resources into a plurality of nodes using natural language parsing to perform word classification based upon parts of speech and so that each node comprises a data structure sufficient to independently convey meaning and including a subject, an attribute, and a bond therebetween,

storing the plurality of nodes in a node pool,

constructing and storing correlations of linked together nodes of the node pool representing knowledge by at least iteratively adding nodes from the node pool onto an end of a chain of nodes by searching the node pool for a match between an attribute of a chained node and a subject of another unchained node in the node pool,

converting the subject, the attribute, and the bond of each node in the node pool into textual objects,

organizing the textual objects from a respective node into a textual phrase to define a note, and

associating notes from each resource into a corresponding note set.

15. The apparatus of claim 14 wherein the organizing comprises associating the subject of the respective node as a note text subject.

16. The apparatus of claim 14 wherein the organizing comprises associating the bond of the respective node as a note text verb.

17. The apparatus of claim 14 wherein the organizing comprises associating the attribute of the respective node as a note text object.

18. An apparatus for identifying knowledge comprising:

an input device for permitting input; and

a processor and memory associated therewith and coupled to said input device for

decomposing resources into a plurality of nodes by using an intermediate format wherein a first term is paired with a second term based upon a relation defined by a context so that each node comprises a data structure sufficient to independently convey meaning and including a subject, an attribute, and a bond therebetween, the context comprising at least one of a schema, a tree graph and a directed graph,

storing the plurality of nodes in a node pool,

constructing and storing correlations of linked together nodes of the node pool representing knowledge by at least iteratively adding nodes from the node pool onto an end of a chain of nodes by searching the node pool for a match between an attribute of a chained node and a subject of another unchained node in the node pool,

converting the subject, the attribute, and the bond of each node in the node pool into textual objects,

organizing the textual objects from a respective node into a textual phrase to define a note, and

associating notes from each resource into a corresponding note set.

19. The apparatus of claim 18 wherein the organizing comprises associating the subject of the respective node as a note text subject.

20. The apparatus of claim 18 wherein the organizing comprises associating the bond of the respective node as a note text verb.

21. The apparatus of claim 18 wherein the organizing comprises associating the attribute of the respective node as a note text object.