Electronic content curating mechanisms

• US 9,189,539 B2
• Filed: 03/15/2013
• Issued: 11/17/2015
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Bastide, Paul R., Broomhall, Matthew E., Loredo, Robert E.
• Primary Examiner(s): Hasan, Syed
• Application Number:
  US13/836,027
• Publication Number:
  US 20140280371A1
• Time in Patent Office: 977 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/35 Clustering; Classification

Abstract

Mechanisms for managing an electronic document collection are provided. A first electronic document is analyzed to identify a reference to a second electronic document and the second electronic document is analyzed to identify document dependencies with zero or more other electronic documents. A dependency information data structure is generated based on the analysis. The dependency information data structure is analyzed to identify a subset of the electronic document collection that is to be loaded into memory when performing an information analysis operation. An electronic document curation action recommendation is generated based on the identified subset of the electronic document collection. The electronic document curation action recommendation is then output.

Claims

1. A method, in a data processing system, for managing an electronic document collection, comprising:

analyzing a first electronic document to identify a reference to a second electronic document;

analyzing the second electronic document to identify document dependencies with zero or more other electronic documents;

generating a dependency information data structure based on the analysis of the first electronic document and the analysis of the second electronic document, wherein the dependency information data structure comprises a dependency graph data structure of the electronic document collection, the dependency graph data structure comprising first nodes representing electronic documents in the electronic document collection, second nodes representing authors of electronic documents in the electronic document collection, and edges between nodes representing relationships between nodes, wherein each of the first nodes and the second nodes have an associated node strength attribute, and wherein the associated node strength attribute is a measure of a relative importance of the associated first node or the associated second node to the dependency graph data structure of the electronic document collection and a fragility of the dependency graph data structure with regard to the associated first node or the associated second node;

analyzing the dependency information data structure to identify a loaded document subset of the electronic document collection that is a subset of electronic documents to be loaded into memory when performing an information analysis operation;

generating an electronic document curation action recommendation based on the identified subset of the electronic document collection; and

outputting the electronic document curation action recommendation.

2. The method of claim 1, further comprising:

analyzing the first electronic document to identify an author of the first electronic document; and

identifying one or more other electronic documents having a same author as the author of the first electronic document, wherein generating the dependency information data structure is further based on the identification of the author of the first electronic document and the identification of the one or more other electronic documents having the same author.

3. The method of claim 1, wherein the node strength attribute of the associated first node or second node in one of the first nodes or the second nodes is calculated based on a number of edges associated with the associated first node or the associated second node.

4. The method of claim 1, wherein the node strength attribute of the associated first node or the associated second node in one of the first nodes or the second nodes is calculated based on at least one of an evaluation of an associated author'"'"'s authority or a veracity of a document associated with the associated first node or the associated second node.

5. The method of claim 4, wherein the node strength attribute of the associated first node or the associated second node is based on the evaluation of the associated author'"'"'s authority, and wherein the evaluation of the associated author'"'"'s authority comprises at least an evaluation of credibility of one or more publications in which the author has published documents and a number of documents published in each of the one or more publications.

6. The method of claim 1, wherein the edges between nodes have associated weight values, and wherein the weight value of an edge is indicative of a strength of a corresponding relationship between nodes associated with the edge.

7. The method of claim 6, wherein the weight value of an edge comprises a base weight value that is calculated based on a number of references from a source document to a referenced document associated with the edge.

8. The method of claim 7, wherein the weight value of the edge is further based on a custom metric applied to the base weight value, and wherein the custom metric is determined based on at least one of a number of edges associated with at least one of a source node or a referenced node associated with the edge, a veracity measure of at least one of the source node or the referenced node associated with the edge, an age of a document associated with at least one of the source node or the referenced node, a determined relative impact of a document associated with at least one of the source node or the referenced node, or positive and negative natural language processing of a document reference in a document associated with the source node.

9. The method of claim 1, wherein the electronic document curation action recommendation comprises at least one of adding an electronic document to the loaded document subset or removing an electronic document from the loaded-document subset.

10. The method of claim 1, wherein the information analysis operation is a question and answer determination operation of a question and answer system in response to the submission of a question by a client computing device.

11. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to:

analyze a first electronic document to identify a reference to a second electronic document;

analyze the second electronic document to identify document dependencies with zero or more other electronic documents;

generate a dependency information data structure based on the analysis of the first electronic document and the analysis of the second electronic document, wherein the dependent information data structure comprises a dependency graph data structure of the electronic document collection, the dependency graph data structure comprising first nodes representing electronic documents in the electronic document collection, second nodes representing authors of electronic documents in the electronic document collection, and edges between nodes representing relationships between nodes, wherein each of the first nodes and the second nodes have an associated node strength attribute, and wherein the associated node strength attribute is a measure of a relative importance of the associated first node or the associated second node to the dependency graph data structure of the electronic document collection and a fragility of the dependency graph data structure with regard to the associated first node or the associated second node;

analyze the dependency information data structure to identify a loaded document subset of the electronic document collection that is a subset of electronic documents to be loaded into memory when performing an information analysis operation;

generate an electronic document curation action recommendation based on the identified subset of the electronic document collection; and

output the electronic document curation action recommendation.

12. The computer program product of claim 11, wherein the computer readable program further causes the computing device to:

analyze the first electronic document to identify an author of the first electronic document; and

identify one or more other electronic documents having a same author as the author of the first electronic document, wherein generating the dependency information data structure is further based on the identification of the author of the first electronic document and the identification of the one or more other electronic documents having the same author.

13. The computer program product of claim 11, wherein the node strength attribute of the associated first node or second node in one of the first nodes or the second nodes is calculated based on a number of edges associated with the associated first node or the associated second node.

14. The computer program product of claim 11, wherein the node strength attribute of the associated first node or the associated second node in one of the first nodes or the second nodes is calculated based on at least one of an evaluation of an associated author'"'"'s authority or a veracity of a document associated with the associated first node or the associated second node.

15. The computer program product of claim 14, wherein the node strength attribute of the associated first node or the associated second node is based on the evaluation of the associated author'"'"'s authority, and wherein the evaluation of the associated author'"'"'s authority comprises at least an evaluation of credibility of one or more publications in which the author has published documents and a number of documents published in each of the one or more publications.

16. The computer program product of claim 11, wherein the edges between nodes have associated weight values, and wherein the weight value of an edge is indicative of a strength of a corresponding relationship between nodes associated with the edge.

17. The computer program product of claim 16, wherein the weight value of an edge comprises a base weight value that is calculated based on a number of references from a source document to a referenced document associated with the edge.

18. The computer program product of claim 17, wherein the weight value of the edge is further based on a custom metric applied to the base weight value, and wherein the custom metric is determined based on at least one of a number of edges associated with at least one of a source node or a referenced node associated with the edge, a veracity measure of at least one of the source node or the referenced node associated with the edge, an age of a document associated with at least one of the source node or the referenced node, a determined relative impact of a document associated with at least one of the source node or the referenced node, or positive and negative natural language processing of a document reference in a document associated with the source node.

19. The computer program product of claim 11, wherein the electronic document aeration action recommendation comprises at least one of adding an electronic document to the loaded document subset or removing an electronic document from the loaded document subset.

20. The computer program product of claim 11, wherein the information analysis operation is a question and answer determination operation of a question and answer system in response to the submission of a question by a client computing device.

21. An apparatus, comprising:

a processor; and

a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to;

analyze a first electronic document to identify a reference to a second electronic document;

analyze the second electronic document to identify document dependencies with zero or more other electronic documents;

generate a dependency information data structure based on the analysis of the first electronic document and the analysis of the second electronic document, wherein the dependency information data structure comprises a dependency graph data structure of the electronic document collection, the dependency graph data structure comprising first nodes representing electronic documents in the electronic document collection, second nodes representing authors of electronic documents in the electronic document collection and edges between nodes representing relationships between nodes, wherein each of the first nodes and the second nodes have an associated node strength attribute, and wherein the associated node strength attribute is a measure of a relative importance of the associated first node or the associated second node to the dependency graph data structure of the electronic document collection and a fragility of the dependency graph data structure with regard to the associated first node or the associated second node;

analyze the dependency information data structure to identify a loaded document subset of the electronic document collection that is a subset of electronic documents to be loaded into memory when performing an information analysis operation;

generate an electronic document curation action recommendation based on the identified subset of the electronic document collection; and

output the electronic document curation action recommendation.