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

SGER：特定领域文本中研究趋势和分类的发现：在纳米科学与工程领域的应用。

• 批准号: 0243579
• 负责人: Abdelghani Bellaachia
• 金额: $ 10万
• 依托单位: George Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-10-15 至 2005-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0243579&HistoricalAwards=false
• 关键词: SGER; Discovery; Research; Trends; Classification

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.

摘要：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，以推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先进技术。 重点领域将是主题和研究趋势的发现以及与所考虑主题相关的数据分类。 对于测试案例，网络上提供的 250,000 个 NSF 奖项的摘要将用作总体数据，分析技术优点和更广泛的影响。