II-NEW: Acquiring infrastructure for Artificial Intelligence, Natural Language Processing and Information Retrieval

University Of Colorado At Colorado Springs, Colorado Springs CO

Investigators

Abstract

This proposal seeks to obtain funding to acquire computing infrastructure to perform cross-disciplinary research in artificial intelligence, natural language processing, bioinformatics, social networks and related fields. In particular, the projects that will be supported by the infrastructure acquired include developing algorithms and architectures for large-scale ontology alignment, particularly in the biomedical domain; mining Wikipedia and similar Web-based sources for geographical, temporal and ontological information; performing named entity recognition in biomedical and other domains; performing computational motivational and content analysis of socially generated content such a blogs and micro-blogs; undertaking corpus-based computational linguistics research in under-studied and possibly endangered languages from India and other locations; developing better-performing algorithms for gene expression analysis; and developing, implementing and comparing algorithms for protein structure prediction, particularly proteins that contain coiled-coil structures. These projects deal with large amounts of data and information and processing such data and information requires large amounts of computing power. Our proposal seeks to acquire adequate and flexible computing hardware to facilitate problem-solving in these and other areas, so that current and future problems can be solved felicitously. The infrastructure acquired will enable cutting-edge research by Ph.D., Masters and undergraduate students, including REU site students, in a variety of cross-disciplinary topics that employ ideas and innovations in artificial intelligence, machine learning and information retrieval. For example, the results of our research may enable creations of systems that discover overlaps and matches among large medical ontologies so that painstakingly created domain-specific information can be fused, compared and utilized better; and may assist in creating programs that assist in automatically understanding and/or visualizing content of socially-generated Websites such as Wikipedia and Twitter. For further information see the project web site at the URL: http://www.cs.uccs.edu/~kalita.