通过语义相关评分操作的定向限定增强信息感知
Enhancing Information Awareness Through Directed Qualification of Semantic Relevancy Scoring Operations
摘要：
成功地管理基于分析的语义关系及其出处可以确定文档的重要性和优先级，进一步提高基于机器的相关性评分操作的能力。语义技术非常适合于对显式和完全合格的关系进行建模，但在对本质上合格的关系或应用分析的结果进行建模时会遇到困难。我们的工作旨在通过将Prov-O Ontology（W3C推荐标准）与支持分析术语的相关性本体配对来实现基于分析的关系的自主定向资格。这项工作的结果是，任何语义引用的文档、概念或命名图都能够与应用分析的结果相关联，作为直接资格（DQ）建模的关系节点。这个新功能将支持角色、身份或任何其他基于内容的相关性度量，以及语义描述文档的基于分析的度量。
英文摘要：
Successfully managing analytics-based semantic relationships and their provenance enables determinations of document importance and priority, furthering capabilities for machine-based relevancy scoring operations. Semantic technologies are well suited for modeling explicit and fully qualified relationships but struggle with modeling relationships that are qualified in nature, or resultant from applied analytics. Our work seeks to implement the autonomous Directed Qualification of analytic-based relationships by pairing the Prov-O Ontology (W3C Recommendation) with a relevancy ontology supporting analytics terminology. This work results in the capability for any semantically referenced document, concept, or named graph to be associated with the results of applied analytics as Direct Qualification (DQ) modeled relational nodes. This new capability will enable role, identity, or any other content-based measures of relevancy and analytics-based metrics for semantically described documents.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
