SGER: Discovery of Research Trends and Classification in Domain-Specific Text: Application to Nanoscale Science and Engineering Field.

这个探索性项目的目标是开发和评估一个系统，以提取、分类和分析专注于纳米科学和工程的奖项。PI将探索基于知识数据发现技术的方法，以促进从大型半结构化数据中提取、分析、理解和消化有关复杂研究领域的信息的最新技术。重点领域将是发现专题和研究趋势以及与审议中专题有关的数据分类。对于测试案例，将使用网络上提供的250,000个NSF奖项的摘要作为总体数据，在那里将分析技术优势以及更广泛的影响。

ABSTRACTThe objective of this exploratory project is to develop and evaluate a system to extract, categorize, and analyze awards focused on nanoscale science and engineering. The PI will explore methods based on knowledge data discovery techniques to advance the state-of-the-art for extracting, analyzing, understanding, and digesting information about a complex research area from large semi-structured data. The areas of focus will be on discovery of topics and research trends and classification of data with respect to the topics under consideration. For the test case, the abstracts of 250,000 NSF awards available on the web will be used as the overall data where both technical merit as well as broader impact will be analyzed.