STTR Phase I: Integrating Online Analytical Processing (OLAP) and Ontologies to Discover Inconsistencies in Expectations for Supply and Demand

STTR 第一阶段：集成在线分析处理（OLAP）和本体以发现供需预期的不一致

• 批准号: 0638323
• 负责人: Peter Moore
• 金额: --
• 依托单位: Clados Management LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-01-01 至 2008-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0638323&HistoricalAwards=false
• 关键词: STTR; Phase; Integrating; Online; Analytical

This Small Business Technology Transfer (STTR) Phase I project aims to produce a software application that enables business people to dramatically improve their ability to forecast supply and demand. In collaboration with the Knowledge Modeling Group at Stanford Medical Informatics, Clados proposes a joint effort to produce relevant aggregation to investigate supply and demand. The effort will proceed in three stages: (1) Capture interactions in OWL from a "training" set of investment research reports; (2) Produce meaningful Online Analytical Processing (OLAP) aggregations on all interactions using the OWL representation directly; and, (3) Evaluate the results by capturing and aggregating interactions from a "control" set of reports.Business people focus heavily on composing narratives to gauge potential supply and demand to guide their investment decisions. In recent years, society has benefited from dramatic increases in volume and availability of information that business people find useful in composing these narratives. However, most people compose those narratives using only the most general tools, predominantly prose documents and spreadsheet tables, and these are insufficient to structure such volume. As a result, society has an opportunity to further improve resource allocation. OLAP technologies may dramatically improve the process of composing narratives to gauge potential supply and demand.

该小型企业技术转让 (STTR) 第一阶段项目旨在开发一款软件应用程序，使企业人员能够大幅提高预测供应和需求的能力。 Clados 与斯坦福医学信息学的知识建模小组合作，提议共同努力生成相关聚合来调查供需。 这项工作将分三个阶段进行：(1) 从一组“训练”投资研究报告中捕获 OWL 中的交互； (2) 直接使用 OWL 表示对所有交互产生有意义的在线分析处理 (OLAP) 聚合； (3) 通过捕获和汇总一组“控制”报告中的交互来评估结果。商界人士非常注重撰写叙述，以衡量潜在的供给和需求，以指导他们的投资决策。近年来，社会受益于信息数量和可用性的急剧增加，商界人士发现这些信息在撰写这些叙述时很有用。然而，大多数人仅使用最通用的工具（主要是散文文档和电子表格）来撰写这些叙述，而这些不足以构建这样的卷。因此，社会有机会进一步改善资源配置。 OLAP 技术可以极大地改进撰写叙述以衡量潜在供应和需求的过程。