INTENT MANAGEMENT TOOL FOR IDENTIFYING CONCEPTS ASSOCIATED WITH A PLURALITY OF USERS' QUERIES

• US 20140324812A1
• Filed: 07/10/2014
• Published: 10/30/2014
• Est. Priority Date: 08/14/2006
• Status: Active Grant

• Current Assignee: Oracle OTC Subsidiary LLC (Oracle Corporation)
• Original Assignee: Oracle OTC Subsidiary LLC (Oracle Corporation)
• Inventors: Cooper, Edwin Riley, Dukes, Michael Peter, Bierner, Gann Alexander, Beghelli, Filippo Ferdinando Paulo
• Granted Patent: US 9,262,528 B2
• Time in Patent Office: Days
• US Class Current: 707/706
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06F 16/3338 Query expansion
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 40/263 Language identification
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

Linguistic analysis is used to identify queries from a plurality of users over a period of time 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. The said intent categories are used in identifying ontologies associated with the intent categories to help in selecting concepts as ontology parameters.

Claims

1. A method, comprising:

receiving a group of electronic representation of questions from a plurality of users over a period of time by an enterprise information system;

identifying groups of the logged questions that use a variety of different linguistic expressions to express similar information requests;

assigning intent categories applicable to each group of questions requesting similar information;

identifying ontologies associated with the intent categories;

assigning concepts in the identified ontologies as ontology parameters for the associated intent categories;

providing intent responses for the ontology parameters assigned to the intent categories;

configuring the intent responses for at least some of the intent categories, wherein each intent response provides applicable information to the questions assigned to the associated intent category;

identifying ones of the intent categories associated with at least a first threshold number of the questions, and providing the intent responses associated with said identified intent categories, wherein said providing is in response to said identification;

identifying ones of the intent categories that are not associated with at least a second threshold number of the questions, and removing intent responses for any of said identified intent categories if currently provided, wherein said removal is in response to said identification; and

for those ones of the intent categories with no associated intent response, identifying ones of the intent categories associated with at least a third threshold number of the questions, and in response to said identification, initiating generation of an intent response for each of said identified intent categories.

2. The method according to claim 1, including using ontology elements associated with the enterprise information system as features for a clustering engine and then using at least some of the cluster names generated by the clustering engine to create the intent categories.

3. The method according to claim 2, including:

identifying queries that do not match any of the created intent categories;

submitting the identified queries to the clustering engine;

generating new cluster names for the clusters of non-matching queries; and

using the new cluster names to generate additional intent categories.

4. The method according to claim 3, including:

automatically generating an intent hierarchy by identifying a new intent category having an associated set of queries that comprise a sub-set of queries for an existing intent category and identifying the new intent category as a child of the existing intent category; and

identifying a new intent category having a subgroup of associated queries that comprise all of the queries matching the existing intent category and identifying the new intent category as a parent of the existing intent category.

5. The method according to claim 2, including processing queries that remain unmatched, said processing including:

identifying relationships between the unmatched queries using the clustering engine;

grouping the unmatched queries according to an output of the clustering engine; and

filtering or ranking the query groupings according to the amount of queries contained therein on a per-group basis, wherein said filtering or ranking identifies a first one of the query groupings having more queries contained therein than a second different one of the filtered query groupings.

6. The method according to claim 5, wherein said processing of the queries that remain unmatched further includes:

outputting a request to correlate the first query grouping with one of the existing intent categories or a new intent category; and

receiving back an input assigning the first query grouping with a particular one of the existing intent categories or the new intent category;

wherein a duration of time passes after assigning the first query grouping where the queries of the second query grouping are unassigned to the intent categories including the new intent category, wherein said duration of time is greater than zero.

7. The method according to claim 1, further comprising:

conducting a spelling analysis to replace unidentifiable words in the questions;

conducting a punctuation analysis to correct punctuation in the questions;

conducting a sentence analysis to identify sentence structures and sentence elements in the questions;

conducting a stem analysis to add and identify other forms of words to the questions;

conducting a concept analysis using one or more ontologies to identify concepts related to the questions; and

conducting a linguistic analysis using the identified concepts, sentence structures, sentence elements, and other added and identified forms of words, wherein the intent category assignment is based on said linguistic analysis.

8. A non-transitory storage medium comprising instructions which, when executed by one or more processors, cause the one or more processors to perform operations comprising:

receiving a group of electronic representation of questions from a plurality of users over a period of time by an enterprise information system;

identifying groups of the logged questions that use a variety of different linguistic expressions to express similar information requests;

assigning intent categories applicable to each group of questions requesting similar information;

identifying ontologies associated with the intent categories;

assigning concepts in the identified ontologies as ontology parameters for the associated intent categories;

providing intent responses for the ontology parameters assigned to the intent categories;

configuring the intent responses for at least some of the intent categories, wherein each intent response provides applicable information to the questions assigned to the associated intent category;

identifying ones of the intent categories associated with at least a first threshold number of the questions, and providing the intent responses associated with said identified intent categories, wherein said providing is in response to said identification;

identifying ones of the intent categories that are not associated with at least a second threshold number of the questions, and removing intent responses for any of said identified intent categories if currently provided, wherein said removal is in response to said identification; and

for those ones of the intent categories with no associated intent response, identifying ones of the intent categories associated with at least a third threshold number of the questions, and in response to said identification, initiating generation of an intent response for each of said identified intent categories.

9. The non-transitory storage medium according to claim 8, wherein the operations further comprise using ontology elements associated with the enterprise information system as features for a clustering engine and then using at least some of the cluster names generated by the clustering engine to create the intent categories.

10. The non-transitory storage medium according to claim 9, wherein the operations further comprise:

identifying queries that do not match any of the created intent categories;

submitting the identified queries to the clustering engine;

generating new cluster names for the clusters of non-matching queries; and

using the new cluster names to generate additional intent categories.

11. The non-transitory storage medium according to claim 10, wherein the operations further comprise:

automatically generating an intent hierarchy by identifying a new intent category having an associated set of queries that comprise a sub-set of queries for an existing intent category and identifying the new intent category as a child of the existing intent category; and

identifying a new intent category having a subgroup of associated queries that comprise all of the queries matching the existing intent category and identifying the new intent category as a parent of the existing intent category.

12. The non-transitory storage medium according to claim 9, wherein the operations further comprise processing queries that remain unmatched, said processing including:

identifying relationships between the unmatched queries using the clustering engine;

grouping the unmatched queries according to an output of the clustering engine; and

filtering or ranking the query groupings according to the amount of queries contained therein on a per-group basis, wherein said filtering or ranking identifies a first one of the query groupings having more queries contained therein than a second different one of the filtered query groupings.

13. The non-transitory storage medium according to claim 12, wherein said processing of the queries that remain unmatched further includes:

outputting a request to correlate the first query grouping with one of the existing intent categories or a new intent category; and

receiving back an input assigning the first query grouping with a particular one of the existing intent categories or the new intent category;

wherein a duration of time passes after assigning the first query grouping where the queries of the second query grouping are unassigned to the intent categories including the new intent category, wherein said duration of time is greater than zero.

14. The non-transitory storage medium according to claim 8, wherein the operations further comprise:

conducting a spelling analysis to replace unidentifiable words in the questions;

conducting a punctuation analysis to correct punctuation in the questions;

conducting a sentence analysis to identify sentence structures and sentence elements in the questions;

conducting a stem analysis to add and identify other forms of words to the questions;

conducting a concept analysis using one or more ontologies to identify concepts related to the questions; and

conducting a linguistic analysis using the identified concepts, sentence structures, sentence elements, and other added and identified forms of words, wherein the intent category assignment is based on said linguistic analysis.

15. A system comprising:

one or more processors; and

one or more non-transitory storage media comprising instructions which, when executed by the one or more processors, cause the one or more processors to perform operations comprising;

receiving a group of electronic representation of questions from a plurality of users over a period of time by an enterprise information system;

identifying groups of the logged questions that use a variety of different linguistic expressions to express similar information requests;

assigning intent categories applicable to each group of questions requesting similar information;

identifying ontologies associated with the intent categories;

assigning concepts in the identified ontologies as ontology parameters for the associated intent categories;

providing intent responses for the ontology parameters assigned to the intent categories;

configuring the intent responses for at least some of the intent categories, wherein each intent response provides applicable information to the questions assigned to the associated intent category;

identifying ones of the intent categories associated with at least a first threshold number of the questions, and providing the intent responses associated with said identified intent categories, wherein said providing is in response to said identification;

identifying ones of the intent categories that are not associated with at least a second threshold number of the questions, and removing intent responses for any of said identified intent categories if currently provided, wherein said removal is in response to said identification; and

for those ones of the intent categories with no associated intent response, identifying ones of the intent categories associated with at least a third threshold number of the questions, and in response to said identification, initiating generation of an intent response for each of said identified intent categories.

16. The system according to claim 15, wherein the operations further comprise using ontology elements associated with the enterprise information system as features for a clustering engine and then using at least some of the cluster names generated by the clustering engine to create the intent categories.

17. The system according to claim 16, wherein the operations further comprise:

identifying queries that do not match any of the created intent categories;

submitting the identified queries to the clustering engine;

generating new cluster names for the clusters of non-matching queries; and

using the new cluster names to generate additional intent categories.

18. The system according to claim 17, wherein the operations further comprise:

automatically generating an intent hierarchy by identifying a new intent category having an associated set of queries that comprise a sub-set of queries for an existing intent category and identifying the new intent category as a child of the existing intent category; and

identifying a new intent category having a subgroup of associated queries that comprise all of the queries matching the existing intent category and identifying the new intent category as a parent of the existing intent category.

19. The system according to claim 15, wherein the operations further comprise processing queries that remain unmatched, said processing including:

identifying relationships between the unmatched queries using the clustering engine;

grouping the unmatched queries according to an output of the clustering engine; and

filtering or ranking the query groupings according to the amount of queries contained therein on a per-group basis, wherein said filtering or ranking identifies a first one of the query groupings having more queries contained therein than a second different one of the filtered query groupings.

20. The system according to claim 19, wherein said processing of the queries that remain unmatched further includes:

outputting a request to correlate the first query grouping with one of the existing intent categories or a new intent category; and

receiving back an input assigning the first query grouping with a particular one of the existing intent categories or the new intent category;

wherein a duration of time passes after assigning the first query grouping where the queries of the second query grouping are unassigned to the intent categories including the new intent category, wherein said duration of time is greater than zero.