Text data mining concerns the application of data mining (knowledge discovery in databases, KDD) to unstructured textual data. Our work focuses on using information extraction to first extract a structured database from a corpus of natural language texts and then discovering patterns in the resulting database using traditional KDD tools. It also concerns record linkage, a form of data-cleaning that identifies equivalent but textually distinct items in the extracted data prior to mining. It is also related to our research on natural language learning. Our recent work has focused on text mining for bioinformatics.

This research was formerly supported by the National Science Foundation through grant IIS-0117308 from the "Information and Data Management" Program.