CONCEPT-BASED ANALYSIS OF STRUCTURED AND UNSTRUCTURED DATA USING CONCEPT INHERITANCE

1 . A method, comprising:

determining a first concept from a first set of data objects, the first concept including a first seed concept and at least one first related concept and defined by a first regular expression indicating (1) a data code in a data object from the first set and (2) a presence of a text string in a data object from the first set;

determining a second concept from a second set of data objects, the second concept including a second seed concept and at least one second related concept and defined by a second regular expression indicating (1) a data code in a data object from the second set and (2) a presence of a text string in a data object from the second set, such that the first concept and the second concept are not positively correlated;

determining a business rule that includes a third regular expression indicating (1) the presence or absence of data code indicative of at least one of the first concept or the second concept in a data object from the first set or a data object from the second set and (2) the presence or absence of a text string indicative of at least one of the first concept or the second concept in a data object from the first set or a data object from the second set;

applying the business rule to a third set of data objects to make a predictive determination for the third set; and

outputting information associated with the predictive determination to a display.

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

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

4 . The method of claim 1 , further comprising:

refining the first concept based on a reference source.

5 . The method of claim 4 , wherein the reference source is a dictionary.

6 . The method of claim 4 , wherein the reference source is a thesaurus.

7 . The method of claim 1 , further comprising:

refining the first concept based on a language relationship.

8 . A method, comprising:

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

defining a business rule including a business rule regular expression indicating (1) the presence or absence of a text string indicative of at least one concept from the plurality of concepts in a data object from the plurality of data objects and (2) the presence or absence of data code indicative of at least one concept from the plurality of concepts in a data object from the plurality of data objects;

applying the business rule to a further set of data objects different from each set of data objects from the plurality of sets of data objects, thereby making a predictive determination of a likelihood of a condition being met based on the set of data objects; and

outputting information associated with the predictive determination to a display.

9 . The method of claim 8 , further comprising

refining at least one concept of the plurality of concepts using a language relationship.

10 . The method of claim 8 , further comprising:

refining at least one concept of the plurality of concepts using a reference source.

11 . The method of claim 10 , wherein the reference source comprises a thesaurus.

12 . The method of claim 10 , wherein the reference source comprises a dictionary.

13 . A method, comprising:

receiving data including a concept hierarchy, the concept hierarchy including a plurality of concepts, each concept from the plurality of concepts including at least one data object;

receiving a first plurality of user input signals, each signal from the plurality of user input signals indicating a selection of at least one concept from the plurality of concepts;

outputting information associated with the plurality of concepts to an output device, wherein the plurality of concepts are not positively correlated;

receiving a second plurality of user input signals that set a plurality of logical relationships between pairs of concepts from the plurality of concepts, based at least in part on a plurality of regular expressions indicating (a) a presence of a text string in a first data object of a first concept of a concept pair or a first data object of a second concept of the concept pair and (b) a data code stored in a second data object of the first concept of the concept pair or a second data object of the second concept of the concept pair,

defining at least one of the plurality of logical relationships as business rule; and

executing the business rule on a set of data objects to make a predictive determination of a likelihood of a condition being met based on the set of data objects.

14 . The method of claim 13 , wherein the set of data objects comprises structured data objects.

15 . The method of claim 13 , wherein the set of data objects comprises unstructured data objects.