Lattice-based confrontation of ontologies

基于格的本体对抗

• 批准号: 249900-2006
• 负责人: Valtchev, Petko
• 金额: $ 1.17万
• 依托单位: Université de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=362699
• 关键词: Lattice; based; confrontation; ontologies

Interoperability of heterogeneous systems on the Web, e.g., two applications exchanging electronic documents, will be admittedly achieved through a confrontation and the subsequent agreement between the underlying ontologies. The most basic confrontation problem, called ontology alignment, reads as follows: given two ontologies each describing a set of entities (concepts, relations), find the relationships (e.g., equivalence or generality) that hold between these entities. Most alignment methods use either similarity or machine learning as tool for detecting plausible alignments and only a small number rely on semantic-based reasoning. They all suffer on specific shortages, ranging from inefficiency to output limitations. As a remedy we shall investigate a novel alignment approach, based on the joint use of concept lattices and similarity, the former as support structure for alignment hypothesis generation and the latter as a ranking mechanism for hypotheses. Concept lattices provide a hierarchical and contextual representation of ontology entity similarities based on shared binary attributes. By binding those attributes to the structural and the terminological aspects of entity descriptions, we expect to approximate the existing semantic relationships between entities and make them appear in the concept lattice as distinctive "patterns". Similarity will then be used to filter the most plausible instances of such patterns before turning them into alignment cells. The ultimate goal is the design of an operational framework for ontology confrontation based on lattices and similarity.

Web上异构系统的互操作性，例如，交换电子文档的两个应用程序将公认地通过底层本体之间的对抗和随后的协议来实现。最基本的对抗问题，称为本体对齐，内容如下：给定两个本体，每个本体描述一组实体（概念，关系），找到关系（例如，（1）这些实体之间的关系。大多数比对方法使用相似性或机器学习作为检测合理比对的工具，只有少数依赖于基于语义的推理。它们都面临着具体的短缺，从效率低下到产量有限。作为一种补救措施，我们将研究一种新的对齐方法，基于概念格和相似性的联合使用，前者作为对齐假设生成的支持结构，后者作为假设的排名机制。概念格基于共享的二进制属性提供本体实体相似性的层次和上下文表示。通过将这些属性绑定到实体描述的结构和术语方面，我们期望近似实体之间的现有语义关系，并使它们在概念格中作为独特的“模式”出现。然后，在将这些模式转换为对齐单元之前，将使用相似性来过滤这些模式的最合理的实例。最终目标是设计一个基于格和相似度的本体对抗操作框架。