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

这项提议寻求获得资金，以获得在人工智能、自然语言处理、生物信息学、社会网络和相关领域进行跨学科研究的计算基础设施。特别是，收购的基础设施将支持的项目包括：为大规模本体比对开发算法和架构，特别是在生物医学领域；挖掘维基百科和类似的基于网络的资源以获取地理、时间和本体信息；在生物医学和其他领域进行命名实体识别；对博客和微博等社会生成的内容进行计算动机和内容分析；用印度和其他地方正在研究的语言以及可能濒危的语言进行基于语料库的计算语言学研究；开发性能更好的基因表达分析算法；以及开发、实施和比较蛋白质结构预测算法，特别是包含卷曲结构的蛋白质。这些项目处理大量的数据和信息，处理这些数据和信息需要大量的计算能力。我们的建议旨在获得足够和灵活的计算硬件，以促进这些领域和其他领域的问题解决，从而使当前和未来的问题能够得到适当的解决。获得的基础设施将使博士、硕士和本科生(包括REU现场学生)能够在各种跨学科主题中进行尖端研究，这些主题利用人工智能、机器学习和信息检索的想法和创新。例如，我们的研究结果可能使发现大型医学本体之间的重叠和匹配的系统得以创建，从而可以更好地融合、比较和利用精心创建的特定领域的信息；并可以帮助创建帮助自动理解和/或可视化诸如维基百科和推特等社交网站的内容的程序。有关更多信息，请参阅项目网站的网址：http://www.cs.uccs.edu/~kalita.

This proposal seeks to obtain funding to acquire computinginfrastructure to perform cross-disciplinary research in artificialintelligence, natural language processing, bioinformatics, socialnetworks and related fields. In particular, the projects that willbe supported by the infrastructure acquired include developing algorithmsand architectures for large-scale ontology alignment, particularly inthe biomedical domain; mining Wikipedia and similar Web-based sourcesfor geographical, temporal and ontological information; performingnamed entity recognition in biomedical and other domains; performingcomputational motivational and content analysis of socially generatedcontent such a blogs and micro-blogs; undertaking corpus-based computationallinguistics research in under-studied and possibly endangered languages fromIndia and other locations; developing better-performing algorithms for geneexpression analysis; and developing, implementing and comparing algorithmsfor protein structure prediction, particularly proteins that containcoiled-coil structures. These projects deal with large amounts of dataand information and processing such data and information requires largeamounts of computing power. Our proposal seeks to acquire adequate andflexible computing hardware to facilitate problem-solving in these and otherareas, 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 avariety of cross-disciplinary topics that employ ideas and innovationsin artificial intelligence, machine learning and information retrieval.For example, the results of our research may enable creations of systemsthat discover overlaps and matches among large medical ontologies so thatpainstakingly created domain-specific information can be fused, comparedand utilized better; and may assist in creating programs that assist inautomatically understanding and/or visualizing content of socially-generatedWebsites such as Wikipedia and Twitter.For further information see the project web site at the URL:http://www.cs.uccs.edu/~kalita.