An Environment for Merging and Testing Large Ontologies
By Deborah L. McGuinness, R. Fikes, James Rice, S. Wilder. International Conference on Principles of Knowledge Representation and Reasoning, 2000
706 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/0b549860adc102548358d0ff1bf51ee4c73e5585
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Natasha Noy
- Ljiljana Stojanović
- Giorgos Flouris
- Jérôme Euzenat
- Dimitris Manakanatas
- Mark A. Musen
- Luis Galárraga
- Yannis Kalfoglou
Citations in the corpus
- Ontologies: How can They be Built? (2004, methodology): “The first tools to help in the fusion process are now available: PROMPT (Noy and Musen 2000) and Chimaera (McGuinness et al. 2000).”
- Methods and tools for ontology evolution (2004, background): “The ontologies, which already exist on the Semantic Web, range from simple taxonomies (such as the Yahoo hierarchy), to metadata schemes (such as the Dublin Core), to logical theories [87].”
- Ontology Matching (2007, background): “Chimaera is a browser-based environment for editing, merging and testing (diagnosing) large ontologies (McGuinness et al. 2000).”
- The PROMPT suite: interactive tools for ontology merging and mapping (2003, methodology): “, iPrompt, Chimaera (McGuinness et al., 2000), OntoMerge (Dou et al.”
- Anchor-PROMPT: Using Non-Local Context for Semantic Matching (2001, methodology): “The Chimaera ontology-merging environment (McGuinness et al. 2000), an interactive merging tool based on the Ontolingua ontology editor (Farquhar et al.”
- Ontology Versioning and Change Detection on the Web (2002, background): “Changes in ontologies do not only affect the data and applications that use them, but they can also have unintended, unexpected and unforeseeable consequences in the ontology itself [16].”
- PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment (2000, methodology): “Chimaera (McGuinness et al. 2000) is an interactive merging tool based on Ontolingua ontology editor (Farquhar et al. 1996).”
- Semantic similarity methods in wordNet and their application to information retrieval on the web (2005, methodology): “Examples of tools for manipulating ontologies include Protege-2000 [34] and Chimaera [25, 26, 27].”
- Ontology change: classification and survey (2008, methodology): “2000), whereas (McGuiness et al. 2000) compares, in the context of merging, the efficiency of a simple plain-text editor, the Ontolingua editor and the specialized tool Chimaera (described in the same paper).”
- User-Driven Ontology Evolution Management (2002, background): “This level of ontology management is necessary not only for the initial development [8] and maintenance of ontologies, but is essential during deployment, when scalability, availability, reliability and performance are absolutely critical [17].”
- A Survey of Schema-Based Matching Approaches (2005, unknown): “At present, there exists a line of semi-automated schema/ontology matching systems, see, for instance [29,25, 14, 32,53, 1, 27, 34,37, 31].”
- Ontology mapping: the state of the art (2003, methodology): “…2002), the SMART , PROMPT and PROMPT-DIFF tools for the Prot¶eg¶e ontology development environment from Noy and Musen, the Chimeara tool (McGuinness et al. 2000), the GLUE (Doan et al. 2002) and CAIMAN (Lacher and Groh 2001) systems, both of which use machine learning, the ITTalks…”
- Fast rule mining in ontological knowledge bases with AMIE+\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$+$$\end{docu (2015, methodology): “Some approaches use rule mining for ontology merging and alignment [12,29,35].”
- AMIE: association rule mining under incomplete evidence in ontological knowledge bases (2013, methodology): “Some approaches use rule mining for ontology merging and alignment [10, 24, 30].”