III-COR-Small: Efficient Matching for Large Real-World Schemas and Ontologies

该项目旨在跨越异构数据，并将影响多个领域的应用，包括应急管理、生物医学、数字政府和环境。特别地，该项目通过测试和评估在异构数据源中建立语义相关概念之间关系的方法和策略，扩展了模式和本体匹配的最新技术，从而扩展了数据集成。本文主要解决以下研究问题：(1)设计在不同粒度（如概念、结构）上运行的模式和本体匹配的方法和算法；(2)开发一个集成系统的原型，除了开发的匹配方法和算法外，该系统还支持大型模式和本体的可视化和操作；(3)对上述方法和系统原型的有效性进行测试和评价，包括准确性（精密度、召回率）和效率（执行时间）。从教育学的角度来看，本项目影响着研究生、本科生和博士后的课程设计和研究训练。关于这个项目的更多信息可以在http://www.cs.uic.edu/~ifc/grants/SchemaOntologyMatching/上找到

III-COR-Small: Efficient Matching for Large Real-World Schemas and OntologiesPI: Maria CruzThis project aims at bridging across heterogeneous data and willimpact applications in multiple fields, including emergencymanagement, biomedicine, digital government, and environment. Inparticular, this project extends the state of the art in schema andontology matching, and therefore in data integration, by testing andevaluating methods and strategies that establish relationships amongsemantically related concepts in heterogeneous data sources.The following research issues are addressed: (1) Design of methods andalgorithms for schema and ontology matching that operate at differentlevels of granularity (e.g., concept, structure); (2) Development of aprototype of an integrated system that supports the visualization andmanipulation of large schemas and ontologies in addition to thedeveloped matching methods and algorithms; (3) Test and evaluation ofthe above methods and system prototype in terms of theireffectiveness, including accuracy (precision, recall) and efficiency(execution time). From an educational viewpoint, this project impactsthe design of courses and the research training of graduate andundergraduate students, and of a postdoc.Further information about this project can be found at:http://www.cs.uic.edu/~ifc/grants/SchemaOntologyMatching/