METHOD AND APPARATUS FOR IDENTIFYING AND CLASSIFYING QUERY INTENT

• US 20130290342A1
• Filed: 06/27/2013
• Published: 10/31/2013
• Est. Priority Date: 08/14/2006
• Status: Active Grant

• Current Assignee: Oracle OTC Subsidiary LLC (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: COOPER, EDWIN RILEY, DUKES, MICHAEL PETER, BIERNER, GANN ALEXANDER, BEGHELLI, FILIPPO FERDINANDO PAULO
• Granted Patent: US 8,898,140 B2
• Time in Patent Office: Days
• US Class Current: 707/740
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06F 40/35 Discourse or dialogue representation
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation

Abstract

Linguistic analysis is used to identify queries that use different natural language formations to request similar information. Common intent categories are identified for the queries requesting similar information. Intent responses can then be provided that are associated with the identified intent categories. An intent management tool can be used for identifying new intent categories, identifying obsolete intent categories, or refining existing intent categories.

Claims

1. A method for classifying a query intent, the method comprising:

providing an ontology that defines a hierarchy of a plurality of concepts at different concept domain layers;

classifying each of a plurality of received queries with a particular intent category based on the ontology, wherein the intent category is pre-defined by a single natural language word or phrase that summarizes a generalized information requested by the queries;

associating an intent response formulated of natural language words or phrases with the particular intent category, wherein the intent response provides a single common applicable response for the queries;

providing an intent hierarchy of a plurality of intent categories including the particular intent category, wherein the intent hierarchy is independent and different from a hierarchy of the ontology;

determining if the particular intent category has a parent hierarchical intent category located in a higher domain layer of the intent hierarchy; and

if the parent hierarchical intent category is present in the particular intent hierarchy, then displaying an intent response of the parent hierarchical intent category.

2. The method of claim 1, wherein said displaying is according to whether a response tag is set for the particular intent category.

3. The method of claim 1, wherein the single natural language word or phrase for the particular intent category does not exist in any of the queries and is not a natural language query for information.

4. The method of claim 1, further comprising:

analyzing how words in the queries are arranged in sentence structures to identify different natural language meanings; and

generating the single natural language word or phrase for the intent category, the single natural language word or phrase both summarizing and paraphrasing the identified different natural language meanings.

5. The method of claim 1, further comprising:

identifying at least some most frequently queried intent categories for the queries; and

providing pre-query intent responses or links for at least a portion of the identified most frequently queried intent categories.

6. The method of claim 5, further comprising:

identifying a first group of new queries that match the identified most frequently queried intent categories; and

providing pre-configured intent responses for the first group of received new queries corresponding with the matching intent categories.

7. The method of claim 6, further comprising:

identifying a second group of new queries that cannot be matched with the identified most frequently queried intent categories;

using a natural language engine and the same or another ontology to identify concepts in the second group of non-matching new queries;

comparing the identified concepts for the second group of new queries with natural language words or phrases for other intent categories; and

providing predetermined responses to any of the second group of new queries matching any of the other intent categories.

8. A system comprising:

a processor; and

a memory coupled with and readable by the processor and storing therein a set of instruction which, when executed by the processor, cause the processor to classify a query intent by;

providing an ontology that defines a hierarchy of a plurality of concepts at different concept domain layers;

classifying each of a plurality of received queries with a particular intent category based on the ontology, wherein the intent category is pre-defined by a single natural language word or phrase that summarizes a generalized information requested by the queries;

associating an intent response formulated of natural language words or phrases with the particular intent category, wherein the intent response provides a single common applicable response for the queries;

providing an intent hierarchy of a plurality of intent categories including the particular intent category, wherein the intent hierarchy is independent and different from a hierarchy of the ontology;

determining if the particular intent category has a parent hierarchical intent category located in a higher domain layer of the intent hierarchy; and

if the parent hierarchical intent category is present in the particular intent hierarchy, then displaying an intent response of the parent hierarchical intent category.

9. The system of claim 8, wherein said displaying is according to whether a response tag is set for the particular intent category.

10. The system of claim 8, wherein the single natural language word or phrase for the particular intent category does not exist in any of the queries and is not a natural language query for information.

11. The system of claim 8, further comprising:

analyzing how words in the queries are arranged in sentence structures to identify different natural language meanings; and

generating the single natural language word or phrase for the intent category, the single natural language word or phrase both summarizing and paraphrasing the identified different natural language meanings.

12. The system of claim 8, further comprising:

identifying at least some most frequently queried intent categories for the queries; and

providing pre-query intent responses or links for at least a portion of the identified most frequently queried intent categories.

13. The system of claim 12, further comprising:

identifying a first group of new queries that match the identified most frequently queried intent categories; and

providing pre-configured intent responses for the first group of received new queries corresponding with the matching intent categories.

14. The system of claim 13, further comprising:

identifying a second group of new queries that cannot be matched with the identified most frequently queried intent categories;

using a natural language engine and the same or another ontology to identify concepts in the second group of non-matching new queries;

comparing the identified concepts for the second group of new queries with natural language words or phrases for other intent categories; and

providing predetermined responses to any of the second group of new queries matching any of the other intent categories.

15. A computer-readable memory comprising a set of instructions stored therein which, when executed by a processor, causes the processor to classify a query intent by:

providing an ontology that defines a hierarchy of a plurality of concepts at different concept domain layers;

classifying each of a plurality of received queries with a particular intent category based on the ontology, wherein the intent category is pre-defined by a single natural language word or phrase that summarizes a generalized information requested by the queries;

associating an intent response formulated of natural language words or phrases with the particular intent category, wherein the intent response provides a single common applicable response for the queries;

providing an intent hierarchy of a plurality of intent categories including the particular intent category, wherein the intent hierarchy is independent and different from a hierarchy of the ontology;

determining if the particular intent category has a parent hierarchical intent category located in a higher domain layer of the intent hierarchy; and

if the parent hierarchical intent category is present in the particular intent hierarchy, then displaying an intent response of the parent hierarchical intent category.

16. The computer-readable memory of claim 15, wherein said displaying is according to whether a response tag is set for the particular intent category.

17. The computer-readable memory of claim 15, wherein the single natural language word or phrase for the particular intent category does not exist in any of the queries and is not a natural language query for information.

18. The computer-readable memory of claim 15, further comprising:

analyzing how words in the queries are arranged in sentence structures to identify different natural language meanings; and

generating the single natural language word or phrase for the intent category, the single natural language word or phrase both summarizing and paraphrasing the identified different natural language meanings.

19. The computer-readable memory of claim 15, further comprising:

identifying at least some most frequently queried intent categories for the queries; and

providing pre-query intent responses or links for at least a portion of the identified most frequently queried intent categories.

20. The computer-readable memory of claim 19, further comprising:

identifying a first group of new queries that match the identified most frequently queried intent categories; and

providing pre-configured intent responses for the first group of received new queries corresponding with the matching intent categories.