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.

随着Web的爆炸性发展和数字图书馆的出现，对半结构化数据的知识发现技术的需求大大增加。半结构化的HTML文档具有丰富的数据模型，即既包含结构化的值，又包含非结构化的概念。探索关于这些非结构化概念之间关系的语义知识是重要的，但作为一个在线过程，博士后助理将帮助开发一个原型Web挖掘系统，该系统将允许用户指定一组约束，或者数据值或概念，并获得一组包含给定约束和与约束集相关的其他项的规则。为了得出这些规则，该系统使用概念库，该概念库区分一般概念和与专业领域相关联的概念。具体地说，助理将1)开发利用库中保留的扩展概念层次来生成部分约束的关联规则和分类规则的新方法，2)调查各种可用的词汇工具并查看如何将它们集成到词网(构成概念库的基础)中，3)探索各种启发式方法来确定一个概念何时属于专业概念库或一般概念库，以及4)探索使用抽样技术来减少规则生成的搜索空间。