15. A computer-implemented method of analyzing at least one database having non-text data in data fields and text in text fields, said method comprising: selecting, by a computing device, by a query a subset of said database based upon search criteria, wherein said subset includes at a plurality of data fields and a plurality of associated text fields; generating, by said computing device, a dictionary comprising terms from said associated text fields, comprising selecting said terms that occur most frequently in said associated text field, such that said terms are selected from results of said selecting of said subset of said database; generating, by said computing device for each term in said dictionary, a probability that each term in said dictionary is independent of said subset; calculating and sorting in order from highest to lowest, a dependency of low-probability terms in said dictionary to said database query terms, wherein said low probability terms have a probability value less than a predetermined maximum probability; identifying, by said computing device, as representative text descriptions, portions of said plurality of associated text fields that include high-dependency terms from said sorting in order from highest to lowest; and outputting, by said computing device, said representative text descriptions that explain an event that was the basis for said database query.
15. A computer-implemented method of analyzing at least one database having non-text data in data fields and text in text fields, said method comprising: selecting, by a computing device, by a query a subset of said database based upon search criteria, wherein said subset includes at a plurality of data fields and a plurality of associated text fields; generating, by said computing device, a dictionary comprising terms from said associated text fields, comprising selecting said terms that occur most frequently in said associated text field, such that said terms are selected from results of said selecting of said subset of said database; generating, by said computing device for each term in said dictionary, a probability that each term in said dictionary is independent of said subset; calculating and sorting in order from highest to lowest, a dependency of low-probability terms in said dictionary to said database query terms, wherein said low probability terms have a probability value less than a predetermined maximum probability; identifying, by said computing device, as representative text descriptions, portions of said plurality of associated text fields that include high-dependency terms from said sorting in order from highest to lowest; and outputting, by said computing device, said representative text descriptions that explain an event that was the basis for said database query. 19. The method in claim 15 , wherein said generating of said dictionary comprises selecting most frequently occurring corpus terms.