Concept-based analysis of structured and unstructured data using concept inheritance

• US 9,245,243 B2
• Filed: 04/14/2009
• Issued: 01/26/2016
• Est. Priority Date: 04/14/2009
• Status: Active Grant

• Current Assignee: CONQ Incorporated
• Original Assignee: Ureveal, inc.
• Inventors: Mohan, Rengaswamy
• Primary Examiner(s): PENG, HUAWEN A
• Application Number:
  US12/423,024
• Publication Number:
  US 20100262620A1
• Time in Patent Office: 2,478 Days
• Field of Search: 707/776, 707/777, 707/778
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2453 Query optimisation
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 40/242 Dictionaries
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

In one embodiment, a method comprises defining a set of concepts based on a first set of structured and unstructured data objects, defining a business rule based on the set of concepts, applying the business rule to a second set of structured and unstructured data objects to make a determination associated with that set, and outputting to a display information associated with the determination.

Claims

1. A method, comprising:

defining a first concept based on a first set of structured and unstructured data objects, the first concept including a first seed concept and at least one first related concept and being defined by a first regular expression indicating (1) a presence of a text string in an unstructured data object from the first set and (2) a data code stored in a structured data object from the first set;

defining a second concept based on a second set of structured and unstructured data objects, the second concept including a second seed concept and at least one second related concept and being defined by a second regular expression indicating (1) a presence of a text string in an unstructured data object from the second set and (2) a data code stored in a structured data object from the second set, wherein the first concept is not positively correlated with the second concept;

defining a business rule to include a third regular expression indicating (1) the presence or absence of a text string indicative of at least one of the first concept or the second concept in an unstructured data object from the first set or from the second set and (2) the presence or absence of data code indicative of at least one of the first concept or the second concept in a structured data object from the first set or from the second set;

applying the business rule to a third set of structured and unstructured data objects to make a prediction indicative of whether the third set satisfies the business rule; and

outputting to a display information associated with the prediction.

2. The method of claim 1, wherein the first set of structured and unstructured data objects and the third set of structured and unstructured data objects are disjoint sets.

3. The method of claim 1, wherein the third set of structured and unstructured data objects is a subset of the first set of structured and unstructured data objects.

4. The method of claim 1, wherein the first concept is included in a first set of concepts, the defining the first concept is performed at a first time, further comprising:

detecting, at a second time, a presence of one or more new concepts in the first set of structured and unstructured data objects that were not present in the first set of structured and unstructured data objects at the first time; and

updating the first set of concepts to include the one or more new concepts.

5. The method of claim 1, wherein the first concept is included in a first set of concepts, the second concept includes one or more concepts from the first set of concepts.

6. The method of claim 1, wherein the defining a first concept includes defining a concept hierarchy based on the first concept.

7. The method of claim 1, further comprising:

refining the first concept using one or more of;

a thesaurus;

a dictionary; and

a language relationship.

8. The method of claim 1, wherein the second relationship can also include one of:

a logical relationship;

a mathematical relationship; and

a relationship based on a linguistic grammar.

9. A method, comprising:

defining a first concept based on a first set of structured and unstructured data objects;

defining a second concept based on the first set, the definition of the second concept based at least in part on at least one structured data element from the first set and at least one unstructured data element from the first set;

defining a third concept based on a second set of structured and unstructured data objects;

defining a fourth concept;

defining a relationship between the first concept and the second concept, the relationship specifying that the second concept is a subconcept of the first concept;

defining a relationship between the second concept and the third concept, the relationship specifying that the second concept is a subconcept of the third concept;

defining, at a first time, a business rule to include a regular expression indicative of a logical relationship between the first concept, the third concept, and the fourth concept;

redefining, at a second time after the first time, the business rule to (1) include a regular expression indicative of a logical relationship between the first concept and the third concept and (2) exclude the fourth concept based on a positive correlation between the fourth concept and one of the first concept or the third concept; and

executing the business rule on a third set of structured and unstructured data objects, the executing including (1) a first determination of a presence of the first concept in the third set, the first determination including a second determination of a presence of the second concept in the third set, and (2) a third determination of a presence of the third concept in the third set, the third determination including a fourth determination of a presence of the second concept in the third set; and

making a prediction indicative of whether the third set satisfies the business rule, the prediction based on the first determination and the third determination; and

outputting to a display information associated with the prediction.

10. The method of claim 9, wherein the business rule includes one or more component parts, each component part being one of:

a regular expression for determining a presence or absence of a concept in an structured or unstructured data object; and

a data code indicating presence or absence of a concept in a structured data object, wherein the executing the business rule includes executing the one or more component parts.

11. The method of claim 9, wherein the first set of structured and unstructured data objects and the third set of structured and unstructured data objects are disjoint sets.

12. The method of claim 9, wherein the third set of structured and unstructured data objects is a subset of the first set of structured and unstructured data objects.

13. The method of claim 9, wherein the first concept or the second concept is a user-defined concept.

14. A method, comprising:

retrieving a concept hierarchy, the concept hierarchy including a first concept, a second concept, and a third concept, the first concept based at least in part on a first set of structured and unstructured data objects;

receiving a first plurality of user input signals, each signal from the plurality of user input signals indicating a selection of one or more of the first concept, the second concept or the third concept;

outputting information associated with the first concept, the second concept and the third concept to a display, wherein the first concept and the third concept are not positively correlated;

receiving a second plurality of user input signals that (1) defines a first logical relationship that is between the first concept and a second concept, the first logical relationship based on a first regular expression indicating (a) a presence of a text string in an unstructured data object the first set or from a second set of structured and unstructured data objects and (b) a data code stored in a structured data object from the first set or from the second set, and (2) defines a second logical relationship that is between the first concept and the third concept, the second logical relationship based on a second regular expression indicating (a) a presence of a text string in an unstructured data object from the first set or from the second set and (b) a data code stored in a structured data object from the first set or from the second set, the second logical relationship defining a business rule; and

executing the business rule on a third set of structured and unstructured data objects to make a prediction whether the second set of structured and unstructured data objects satisfies the business rule.

15. The method of claim 14, further comprising:

receiving a third plurality of user input signals responsive to the information, each user input signal from the third plurality including indication of a desired change to a definition of the one or more of the first concept, the second concept or the third concept; and

updating the definition of the one or more of the first concept, the second concept and the third concept based on the third plurality of user input signals.

16. The method of claim 14, further comprising:

analyzing the concept hierarchy to detect a presence of one or more relationships between the first concept, the second concept and the third concept; and

updating the concept hierarchy to define the one or more relationships.

17. The method of claim 14, further comprising:

applying the business rule to one or more sets of test data;

generating one or more reports based on the applying;

receiving a user input signal responsive to the one or more reports, the user input signal indicating a desired change to the business rule; and

updating the business rule to effectuate the desired change.

18. The method of claim 14, wherein the first set of structured and unstructured data objects and the second set of structured and unstructured data objects are disjoint sets.