The knowledge discovery research projects funded by TRECC in 2004 focus on identifying and extracting large, new, and useful patterns of information from large data collections using data mining algorithms. The ultimate goal of these projects, however, is to go beyond data mining to facilitate decision-making and collaboration through emphasis both on human-human and human-machine interaction.

DISCUS: Distributed Innovation and Scalable Collaboration in Uncertain Settings
DISCUS is intended to accelerate the human decision-making process in dynamic circumstances by integrating both human- and computer-generated knowledge in a scalable, distributed collaborative environment.

Mining Hidden Networks and Sequential Patterns
The goal of this research is to construct a user-oriented hidden network and sequential pattern miner for effective and scalable pattern discovery and application development. The work will integrate social network analysis, linkage analysis, sequential and graph pattern mining methods.

Cross-Document Entity Identification and Training
Theoretical and algorithmic approaches are being developed to support an intelligent text analysis tool for identifying entities of interest and different mentions of them, and for tracing of entities and information relevant to them within and across documents.