SBIR Phase IB: Units-based numeric data extraction with knowledge of scientific context

这个小企业创新研究第一阶段项目的重点是一种新的方法来开发基于单位的数字索引和搜索工具。目标是从技术文献中提取数字量，用相应的物理单位识别每个数字量，并进一步将这些数字量与其他已识别的语义实体（如设备属性）相关联。与试图用人工智能学习算法识别模糊结构的通用语义信息提取策略不同，纠缠技术？解决方案利用了单位的标准化和通用性。在知识丰富的背景下，通过科学计量学可以准确地识别物理量，因此数字搜索比关键字搜索更有效。研究的目标是设计和优化这些科学算法在广泛的物理单元，智能地提取数值数据。同时，Entanglement将开发详细的科学本体，用于识别索引数字单位对的上下文。该项目的成功示范为技术和科学规格的快速和准确的数据挖掘提供了可能。这将在工业和科学研究中有广泛的应用。Entanglement Technologies预计将通过使用这种搜索技术获得许可收入，目标是参与高科技投资的金融机构和提供科学搜索能力的学术图书馆。能够定义全面的，但客观的，上下文的数字排除了用户的责任，确定搜索引擎的正确性？s检索。这一固有特征为非专家提供了搜索、汇总和分析目前仅由专家处理的技术数据的能力。此外，基于单位的数字搜索提供了自动数字提取和聚合的可能性。Entanglement将利用此功能，将其搜索功能集成到前端用户友好的包中，使客户不仅可以从搜索中受益，还可以从简化的图形和报告生成中受益。如果成功，这种自动化的潜力将降低目前由技术咨询公司提供的这种服务的成本。

This Small Business Innovation Research Phase I project focuses on a novel approach to develop units-based numeric indexing and search tools. The goal is to extract numeric quantities from technical literature, identify each with a corresponding physical unit, and further relate these to other identified semantic entities such as device properties. Unlike generic semantic information extraction strategies, which attempt to identify ambiguous structure with AI learning algorithms, Entanglement Technologies? solution capitalizes on the standardization and universality of units. Physical quantities are identified accurately with scientific heuristics in knowledge-rich contexts, and thus numeric search can be more efficient than keyword searches. The research objectives are to design and optimize these scientific heuristics across a wide array of physical units to intelligently extract numeric data. Concurrently, Entanglement will develop detailed scientific ontologies for identifying the context of an indexed number-unit pair. Successful demonstration of this project offers the potential for rapid and accurate data mining for technical and scientific specifications. This will have broad applications in industrial and scientific research. Entanglement Technologies anticipates generating licensing revenue from access to this search technology, targeting financial institutions involved in high-tech investments and academic libraries providing scientific search capabilities. The ability to define comprehensive, yet objective, heuristics for contextualizing a number removes much of the user's responsibility for identifying the correctness of the search engine?s retrieval. This inherent feature provides a non-expert with the capability for searching, aggregating and analyzing technical data currently only processed by experts. Furthermore, units-based numeric search offers the potential for automated number extraction and aggregation. Entanglement will utilize this capability by integrating its search functionality into a front-end user-friendly package, allowing a customer to benefit not only from the search but also from streamlined graph and report generation. If successful, this potential for automation will reduce the cost of such services currently provided by technical consulting firms.