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-0000536 Scheuermann，Peter西北大学CISE实验计算机科学博士后研究员：Web上半结构化数据挖掘的体系结构随着Web的爆炸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HTML文档具有丰富的数据模型，即，它们包含结构化的值和非结构化的概念。 探索这些非结构化的概念之间的关系的语义知识是重要的，但昂贵的在线process.The博士后助理将协助开发一个原型Web miningsystem，将允许其用户指定一组约束条件，eitherdata值或概念，并获得一组规则，包含givenconstraints和其他项目的约束集。 为了得到这些规则，系统利用了一个概念库，它区分了一般概念和与专门领域相关的概念。 具体地说，助理将1）开发新的方法来生成部分约束的关联规则和分类规则，这些规则利用了库中保存的扩展概念层次结构，2）研究各种可用的词汇工具，并了解如何将它们集成到Wordnet中（这构成了概念库的基础），3）探索各种启发式方法来确定给定概念属于特定概念库还是属于一般概念库，（4）探索抽样技术在减少规则生成搜索空间中的应用。