SGER: CS-BibCube: OLAPing and Mining of Computer Science Literature

SGER：CS-BibCube：计算机科学文献的 OLAP 和挖掘

• 批准号: 0842769
• 负责人: Jiawei Han
• 金额: $ 10.5万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2010-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0842769&HistoricalAwards=false
• 关键词: SGER; CS; BibCube; OLAPing; Mining

This goal of this research project is to investigate issues in the design and development of CS-BibCube, a multidimensional text data cube, constructed based on multidimensional categorical dimensions (e.g., author list, venue, and date) and unstructured text attributes (e.g., title, abstract, and contents), to facilitate multidimensional online analytical processing (OLAP) and mining of computer science literature. Data cube has become an essential engine in data warehouse industry and has been extended to handle relatively structured non-relational data, including spatio-temporal data, sequences, graphs, data streams, etc. However, it is still challenging to handle unstructured text data. This project is to explore and evaluate the possibilities and alternatives on the design, multidimensional modeling, implementation, performance improvement, and deployment of text-cubing and text-OLAP. The work will integrate multiple disciplinary approaches derived from data cube and OLAP, information retrieval, text mining, and machine learning, and further study is expected to be expanded to other multidimensional text databases with broad applications in business, industry, government agencies, scientific research, and education. The research results are to be published in research forums on information retrieval, data mining, and database systems, and be integrated into the educational program at the University of Illinois at Urbana-Champaign. The progress of the project and the research results will be disseminated via the project Web site (http://www.cs.uiuc.edu/~hanj/projs/csbibcube.htm).

本研究项目的目标是研究 CS-BibCube 的设计和开发问题，CS-BibCube 是一个多维文本数据立方体，基于多维分类维度（例如，作者列表、地点和日期）和非结构化文本属性（例如，标题、摘要和内容）构建，以促进多维在线分析处理（OLAP）和计算机科学文献的挖掘。数据立方已成为数据仓库行业的重要引擎，并已扩展到处理相对结构化的非关系数据，包括时空数据、序列、图、数据流等。然而，处理非结构化文本数据仍然具有挑战性。该项目旨在探索和评估文本立方和文本OLAP的设计、多维建模、实现、性能改进和部署的可能性和替代方案。这项工作将整合源自数据立方体和OLAP、信息检索、文本挖掘和机器学习的多种学科方法，进一步的研究预计将扩展到其他多维文本数据库，在商业、工业、政府机构、科学研究和教育领域有广泛的应用。研究结果将发表在信息检索、数据挖掘和数据库系统的研究论坛上，并纳入伊利诺伊大学厄巴纳-香槟分校的教育计划中。项目进展和研究成果将通过项目网站（http://www.cs.uiuc.edu/~hanj/projs/csbibcube.htm）传播。