SGER: Discovery of Research Trends Using Concept Extraction and Data Mining Techniques in domain-specific Text: Application to Nanoscale Science and Engineering Field.

美国国家科学基金会-化学运输系统分部颗粒多相过程计划（1415）提案编号：0737961主要研究员：贝拉契亚，A。 所属单位： 乔治华盛顿大学提案题目：SGER：在特定领域使用概念提取和数据挖掘技术发现研究趋势文本：应用于纳米科学与工程领域本项目的目的是进行探索性研究，采用知识数据发现技术，将推进提取，分析，理解，以及从大型半结构化数据中提取关于复杂研究领域的信息。当搜索包含要查找的数据或主题的文档时，搜索只包含一个关键字匹配。在过去，这种技术是成功的，因为可能会返回的文件数量。然而，现在有数万亿可能的文件，适合简单的关键字搜索，一个更充分的方法需要开发。概念提取可能是一个可能的解决方案，这个日益增长的问题。概念提取是以编程方式检查文档并确定其主题或关键思想的过程。本研究将使用概念撷取与资料探勘技术来分析线上NSF奖项，并以奈米尺度的科学与工程奖项为重点。名词短语将使用现有的工具，如通用文本工程架构（GATE）[10]从奖项提案中提取。名词短语列表将用于描述每个奖项的内容。本项目将解决两个主要问题：（1）主题和研究趋势的发现，以及（2）根据这些主题对数据进行分类。我们的系统的评估将使用在线NSF奖项进行，并将针对纳米级的科学和工程awards.Intellectual MeritThis研究解决的问题和机会，提出了越来越复杂的大型半结构化数据，可在商业，科学和一系列其他领域。当前的搜索技术不提供直观的机制来导航数据集中的不同主题。从我们以前的努力最显着的贡献是建立数据库，存储所有纳米级科学和工程奖项与不同的功能。本计画的研究目标是实现一个资料探勘工具，以侦测奈米级科学与工程领域的新兴研究趋势。这个工具将使用算法，足以这种类型的应用领域。更广泛的影响所提出的工作的更广泛的影响也是许多以及显着的。我们的研究可以应用到其他领域，如生物信息学。我们的研究涉及到教育过程中的以下更广泛的影响：-拟议的活动将为研究生和/或本科生提供支持。这项研究的结果将通过会议和/或期刊出版物以及讲座和研讨会广泛传播。最后，本研究所采用的方法将与我的数据挖掘班的学生分享。

National Science Foundation - Division of Chemical &Transport Systems Particulate & Multiphase Processes Program (1415)Proposal Number: 0737961 Principal Investigator: Bellaachia, A. Affiliation: George Washington University Proposal Title: SGER: Discovery of Research Trends Using Concept Extraction and Data Mining Techniques in domain-specific Text: Application to Nanoscale Science and Engineering Field The purpose of this project is to conduct exploratory research, employing knowledge data discovery techniques that will advance the state-of-the art for extracting, analyzing, understanding, and digesting information about a complex research area from large semi-structured data. When searching for documents that contain the data or topics that one is looking for, the search consists of little more than a keyword matching. In the past this technique has been successful, due to the number of documents that could possibly be returned. However, now that there are trillions of possible documents that fit simple keyword searches, a more sufficient methodology needs to be developed.Concept extraction could be a possible solution to this growing problem. Concept extraction is the process of examining a document programmatically and determining its subject or key ideas. This research will use concept extraction and apply data mining techniques to analyze the online NSF awards with a focus on the nano-scale science and engineering awards. Noun phrases will be extracted from award proposals using existing tools such as General Architecture for Text Engineering (GATE) [10]. The list of noun phrases will be used to describe the content of each award. Two main issues will be addressed in this project (1) the discovery of topics and research trends, and (2) the classification of data according to these topics. The evaluation of our system will be conducted using the online NSF awards and will target the nanoscale scientific and engineering awards.Intellectual MeritThis research addresses problems and opportunities presented by the increasingly complex large semi-structured data available in business, science, and a range of other domains. Current searching techniques do not provide intuitive mechanisms to navigate through different topics in the dataset. The most significant contribution from our previous effort was the establishment of database that stores all nanoscale science and engineering awards with different functionalities. The research objectives of this project are to implement a data mining tool that detects emergent research trends in the area of nanoscale science and engineering fields. This tool will use algorithms that adequate to this type of domain of applications.Broader ImpactThe broader implications of the proposed work are also many as well as significant. Our research can be applied to other domains such bio-informatics. The following broader implications of our research relate to the educational process:- The proposed activity will provide support for graduate and/or undergraduate students.- The findings of this research will be disseminated broadly via conferences and/or journal publications as well as lectures and seminars as opportunities arise.- Finally, the methodology followed in this research will be shared with the students of my data mining class.