Systems and methods for performing non-binary classification during sequence mining

Abstract

Systems and methods recite a system that expands the available amount of data that may be used for training and/or detecting cyber fraud. In particular, as opposed to limiting training data (and/or successful matches) to patterns of text strings in electronic communications of user records, the systems and methods additionally generate training data (and/or successful matches) on the characteristics of the text strings themselves (e.g., the specific characters used, the length, the uniqueness of the text string, etc.). Moreover, the systems and methods may determine particular rules that an identified text string and/or characteristics thereof violates. The system may then use instances of the identified text string, characteristics thereof, and/or violated rule to supplement existing training data. Thus, the systems and methods mitigate the technical problem related to the limited training data.