1. 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, a subset of said database based upon a database query, wherein said subset includes 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; 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, as representative text descriptions, by said computing device, 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.
1. 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, a subset of said database based upon a database query, wherein said subset includes 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; 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, as representative text descriptions, by said computing device, 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. 5. The method in claim 1 , wherein said generating of said dictionary comprises selecting most frequently occurring corpus terms.