Topic
Upper ontology
About: Upper ontology is a research topic. Over the lifetime, 9767 publications have been published within this topic receiving 220721 citations. The topic is also known as: top-level ontology & foundation ontology.
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TL;DR: A model for linguistic grounding of ontologies called LexInfo, implemented as an OWL ontology and freely available together with an API, which allows us to associate linguistic information to elements in an ontology with respect to any level of linguistic description and expressivity.
147 citations
TL;DR: This paradigm based on the idea of harvesting the Semantic Web, i.e., automatically finding and exploring multiple and heterogeneous online knowledge sources to derive mappings, has a promising baseline precision of 70% and is complementary to existing techniques.
Abstract: In this paper we propose an ontology matching paradigm based on the idea of harvesting the Semantic Web, i.e., automatically finding and exploring multiple and heterogeneous online knowledge sources to derive mappings. We adopt an experimental approach in the context of matching two real life, large-scale ontologies to investigate the potential of this paradigm, its limitations, and its relation to other techniques. Our experiments yielded a promising baseline precision of 70% and identified a set of critical issues that need to be considered to achieve the full potential of the paradigm. Besides providing a good performance as a stand-alone matcher, our paradigm is complementary to existing techniques and therefore could be used in hybrid tools that would further advance the state of the art in the ontology matching field.
146 citations
Patent•
06 Oct 2000
TL;DR: In this paper, an ontology-based approach is proposed to generate Java-based object-oriented and relational application program interfaces (APIs) from a given ontology, providing application developers with an API that exactly reflects the entity types and relations (classes and methods) that are represented by the database.
Abstract: A system and method lets a user create or import ontologies and create databases and related application software. These databases can be specially tuned to suit a particular need, and each comes with the same error-detection rules to keep the data clean. Such databases may be searched based on meaning, rather than on words-that-begin-with-something. And multiple databases, if generated from the same basic ontology can communicate with each other without any additional effort. Ontology management and generation tools enable enterprises to create databases that use ontologies to improve data integration, maintainability, quality, and flexibility. Only the relevant aspects of the ontology are targeted, extracting out a sub-model that has the power of the full ontology restricted to objects of interest for the application domain. To increase performance and add desired database characteristics, this sub-model is translated into a database system. Java-based object-oriented and relational application program interfaces (APIs) are then generated from this translation, providing application developers with an API that exactly reflects the entity types and relations (classes and methods) that are represented by the database. This generation approach essentially turns the ontology into a set of integrated and efficient databases.
145 citations
Proceedings Article•
22 Jul 2007TL;DR: The problem of errors in mappings is addressed by proposing a completely automatic debugging method that uses logical reasoning to discover and repair logical inconsistencies caused by erroneous mappings.
Abstract: Automatically discovering semantic relations between ontologies is an important task with respect to overcoming semantic heterogeneity on the semantic web. Existing ontology matching systems, however, often produce erroneous mappings. In this paper, we address the problem of errors in mappings by proposing a completely automatic debugging method for ontology mappings. The method uses logical reasoning to discover and repair logical inconsistencies caused by erroneous mappings. We describe the debugging method and report experiments on mappings submitted to the ontology alignment evaluation challenge that show that the proposed method actually improves mappings created by different matching systems without any human intervention.
144 citations
10 May 2005
TL;DR: The proposed extraction method is a helpful tool to support the process of building domain ontologies for web service descriptions and is conducted in the field of bioinformatics by learning an ontology from the documentation of the web services used in myGrid, a project that supports biology experiments on the Grid.
Abstract: The reasoning tasks that can be performed with semantic web service descriptions depend on the quality of the domain ontologies used to create these descriptions. However, building such domain ontologies is a time consuming and difficult task.We describe an automatic extraction method that learns domain ontologies for web service descriptions from textual documentations attached to web services. We conducted our experiments in the field of bioinformatics by learning an ontology from the documentation of the web services used in myGrid, a project that supports biology experiments on the Grid. Based on the evaluation of the extracted ontology in the context of the project, we conclude that the proposed extraction method is a helpful tool to support the process of building domain ontologies for web service descriptions.
143 citations