CISE Postdoctoral Research Associateships in Experimental Computer Science - An Architecture for Mining of Semi-Structured Data on the WEB

CISE 实验计算机科学博士后研究奖学金 - 网络上半结构化数据挖掘的架构

• 批准号: 0000536
• 负责人: Peter Scheuermann
• 金额: $ 6.6万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2003-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0000536&HistoricalAwards=false
• 关键词: CISE; Postdoctoral; Research; Associateships; Experimental

EIA-0000536Scheuermann, PeterNorthwestern UniversityCISE Postdoctoral Associates in Experimental Computer Science: AnArchitecture for Mining of Semi-Structured Data on the WebWith the explosion of the Web and the advent of digital libraries, thedemand for knowledge discovery techniques for semi-structured data hasincreased greatly. Semi-structured HTML documents are characterized by arich data model, i.e., they contain both structured values and unstructuredconcepts. Exploring the semantic knowledge about the relationships amongthese unstructured concepts is important but costly as an on-line process.The postdoctoral associate will assist in developing a prototype Web miningsystem that will allow its users to specify a set of constraints, eitherdata values or concepts, and obtain a set of rules that contain the givenconstraints and other items related to the constraint set. In order toderive these rules, the system makes use of a concept library thatdifferentiates between general concepts and concepts associated withspecialized domains. Specifically, the associate will 1) develop newmethods for generating partially constrained association rules andclassifications rules that make use of the extended concept hierarchieskept in the library, 2) investigate the various lexical tools available andsee how to integrate them into Wordnet (which forms the basis of theconcept library), 3) explore various heuristic methods for deciding when agiven concept belongs to a specialized concept library or to the generalconcept library, and 4) explore the use of sampling techniques in reducingthe search space of rule generation.

EIA-0000536SCHEUERMANN，PETERNORTHWESTERN UNIVESSIONCISE实验计算机科学的博士后协会：用于挖掘网络上半结构化数据的无政府状态，网络爆炸和数字图书馆的出现，对于半结构的数据，用于半结构的数据的知识发现技术。 半结构化的HTML文档的特征是Arich数据模型，即它们既包含结构化值和非结构化概念。 探索有关这些非结构化概念之间关系的语义知识很重要，但作为在线过程中的成本很高。博士后合伙人将有助于开发一个原型的Web Miningsystem，该系统将允许其用户指定一组约束，Data值或概念，并获得包含与givenConstraints和其他项目相关的规则和其他相关的规则。 为了使这些规则旨在使用这些规则，该系统利用一个概念库，该概念库在与特定域相关的一般概念和概念之间存在分化。 具体而言，同事将为1）开发新的方法，以生成部分约束的关联规则和阶级规则，以利用图书馆中的扩展概念层次结构，2）研究可用的各种词汇工具，并看到如何将它们集成到WordNet中（构成了库的概念，以构成了库的概念，3），3），3），3），3），3），3），3），3） 4）探索采样技术在减少规则生成的搜索空间中的使用。