GUIDED NAVIGATION SYSTEM

• US 20070282769A1
• Filed: 05/10/2006
• Published: 12/06/2007
• Est. Priority Date: 05/10/2006
• Status: Active Grant

• Current Assignee: Oracle OTC Subsidiary LLC (Oracle Corporation)
• Original Assignee: Inquira Incorporated (Oracle Corporation)
• Inventors: Bierner, Gann
• Granted Patent: US 7,921,099 B2
• Time in Patent Office: Days
• US Class Current: 706/20
• 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: G06F 16/93 Document management systems
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation

Abstract

A navigation system is used in combination with a data retrieval system to more effectively locate the correct answers or information in search content. The navigation system provides taxonomies that identify different information categories and sub-categories (facets). Classifiers automatically classify the search content by identifying the content corresponding with associated facets. The facets, in conjunction with the associated classifiers, provide robust classification and correlation between both structured and unstructured content. Rules can be used in conjunction with the facets and classifiers to automatically control different navigation operations. The navigation system can also leverage ontologies to dynamically create taxonomies and provides unique facet expansion and intra-document classification operations.

Claims

1. A method for classifying content, comprising:

receiving both structured and unstructured content;

providing a taxonomy having facets associated with different subject categories;

using a structured classifier to classify the structured content with one of the facets; and

using a unstructured classifier to classify the unstructured content with the facet.

2. The method according to claim 1 wherein the structured classifier searches predetermined data fields or predefined locations in the structured content for information associated with the facet.

3. The method according to claim 1 wherein the unstructured classifier searches for information associated with the facet that is not located in predefined data fields or predefined locations in the unstructured content.

4. The method according to claim 3 including using an Intelligent Matching Language (IML) in the unstructured classifier to search data items in the unstructured content corresponding with a concept identified by the facet.

5. The method according to claim 1 including:

assigning identifiers to data items in both the structured and unstructured content;

using the structured classifier to generate a list of the identifiers for the data items in the structured content associated with the facet;

using the unstructured facet classifier to add the identifiers to the same list for the data items in the unstructured content associated with the facet; and

displaying the number of data items in both the structured and unstructured content associated with the same facet by counting the number of identifiers in the list that are possible answers to a query.

6. The method according to claim 1 including:

identifying data items in either the structured or unstructured content associated with the facet;

identifying different sub-categories for the identified data items;

building a new taxonomy by listing the sub-categories underneath the facet; and

classifying the data items according to the new taxonomy.

7. The method according to claim 1 including:

associating an ontology with the structured and unstructured content that includes at least one concept having different categories and sub-categories;

inserting a portion of the ontology into the taxonomy; and

using the categories and sub-categories for the extracted portion of the ontology as facets for classifying the structured and unstructured content.

8. The method according to claim 7 including:

building new classifiers for the facets created from the ontology; and

using the new classifiers to classify the content with the facets created from the ontology.

9. The method according to claim 7 including:

conducting a query that returns search results;

comparing concept categories in the ontology with data items contained in the search results;

identifying the concepts categories associated with the data items from the search results; and

dynamically creating facets in the taxonomy according to the concept categories in the ontology corresponding with the search results.

10. A computing system, comprising:

a processor configured to receive both structured and unstructured content and classify both the structured and unstructured content into categories identified in an associated taxonomy.

11. The computing system according to claim 10 wherein the processor is further configured to independently operate both structured and unstructured classifiers for the same taxonomy categories, the structured classifiers classifying the structured content for associated taxonomy categories and the unstructured classifiers classifying the unstructured content for associated taxonomy categories.

12. The computing system according to claim 10 wherein the processor is configured to identify at least some of the taxonomy categories as concepts and then operate an Intelligent Matching Language (IML) that identifies the taxonomy category concepts with data items in the structured and/or unstructured content.

13. The computing system according to claim 10 including memory that contains lists associated with the taxonomy categories, the processor configured to classify data items in both the structured and unstructured content with the taxonomy categories and then store identifiers for the classified items in the lists associated with the taxonomy categories.

14. The computing system according to claim 13 wherein the processor tracks a number of identifiers contained in the lists associated with the taxonomy categories and displays the number on a User Interface (UI) along side the associated taxonomy categories.

15. The computing system according to claim 10 wherein the processor is configured to automatically generate sub-categories for one or more of the taxonomy categories and then classify both the structured and unstructured content for both the taxonomy categories and taxonomy sub-categories.

16. The computing system according to claim 15 wherein the processor is further configured to automatically create classifiers for the generated taxonomy sub-categories that then automatically identify data items in the structured and unstructured content associated with the taxonomy sub-categories.

17. The computing system according to claim 10 wherein the processor is configured to provide an ontology that includes different ontology categories and ontology sub-categories, the processor inserting a portion of the ontology into the taxonomy and classifying the structured and unstructured content using the categories and sub-categories extracted from the ontology.

18. The method according to claim 17 wherein the processor is configured to compare concepts identified in the ontology with data items in the structured and/or unstructured content and identify the concepts in the ontology that are associated with the data items, the processor then configured to automatically create the taxonomy according to the identified concepts in the ontology.

19. A method for building taxonomies in a document navigation system, comprising:

identifying one or more taxonomy categories for classifying content received back from a query;

automatically building taxonomy sub-categories from a portion of an existing ontology to provide sub-classifications of the identified taxonomy categories; and

using the taxonomy categories and built taxonomy sub-categories to automatically classify the content received back from the query.

20. The method according to claim 19 including identifying the one or more taxonomy categories from an existing taxonomy and then dynamically generating the taxonomy sub-categories at run time from data items received back from a query and initially classified using the existing taxonomy categories.

21. The method according to claim 19 including building classifiers that automatically classify the content for the built taxonomy categories and/or sub-categories.

22. The method according to claim 21 including:

identifying data items in the content associated with the ontology;

analyzing the different types of concepts and/or words in the ontology that are associated with the identified data items; and

dynamically creating a taxonomy according to the different types of concepts and/or other types of non-concept words in the ontology that are associated with the data items.

23. A computer readable medium containing instructions that when executed, comprise:

receiving both structured and unstructured content;

providing a taxonomy having facets associated with different subject categories;

using a structured classifier to classify the structured content with one of the facets; and

using a unstructured classifier to classify the unstructured content with the facet.

24. The computer readable medium according to claim 23 wherein the structured classifier searches predetermined data fields or predefined locations in the structured content for information associated with the facet.

25. The computer readable medium according to claim 23 wherein the unstructured classifier searches for information associated with the facet that is not located in predefined data fields or predefined locations in the unstructured content.

26. The computer readable medium according to claim 23 including instructions that use an Intelligent Matching Language (IML) in the unstructured classifier to search data items in the unstructured content corresponding with a concept identified by the facet.

27. The computer readable medium according to claim 23 including instructions that when executed:

identify data items in either the structured or unstructured content associated with the facet;

identify different sub-categories for the identified data items;

build a new taxonomy by listing the sub-categories underneath the facet; and

classify the data items according to the new taxonomy.

28. The computer readable medium according to claim 23 including instructions that when executed:

associate an ontology with the structured and unstructured content that includes at least one concept having different categories and sub-categories;

insert a portion of the ontology into the taxonomy; and

use the categories and sub-categories for the extracted portion of the ontology as facets for classifying the structured and unstructured content.

29. The computer readable medium according to claim 28 including instructions that when executed:

build new classifiers for the facets created from the ontology; and

use the new classifiers to classify the content with the facets created from the ontology.

30. The computer readable medium according to claim 29 including instructions that when executed:

conduct a query that returns search results;

compare concept categories in the ontology with data items contained in the search results;

identify the concepts categories associated with the data items from the search results; and

dynamically creating facets in the taxonomy according to the concept categories in the ontology corresponding with the search results.