EAGER: Network Pattern Recognition Project

University Of California-Berkeley, Berkeley CA

Investigators

Abstract

This project proposes to explore integrated methodologies for pattern discovery and network analysis in multi-lingual text corpora. The interdisciplinary project team will focus on recent developments in network analysis of complex problems associated with visual query systems, topic discovery, anomaly detection, and rapid mining of complex time-stamped data as a means for extending approaches to noisy data from a range of disciplinary source materials. In order to look at the various problems and solutions to these major issues in current scholarship, the PIs have chosen three sets of disparate data: Buddhist Canonic texts (Chinese and Sanskrit); Irish studies journals (English and Gaelic); and Danish folklore (English and Danish). The research exercise to be performed is of a scale and complexity never before attempted. The project anticipates finding deficiencies in existing network analysis algorithms dealing with rich external data available on nodes and links and developing new network analysis algorithms to overcome the deficiencies.