The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We argue that it is more practical to address the ontology mapping self-tuning problem in a whole system context instead of in a single matcher context. In this paper we introduce RMOMS, a Reference Model for Ontology Mapping Systems, consisting of six parts, the Preprocessor, the Dispatcher, the Matcher(s), the Aggregator, the Pruner, and the User Interface, with which to disassemble the self-tuning...
The method of component description and retrieval is a hot subject of research in component-based software development. In order to describe the component more completely and accurately, an approach based facet and ontology is brought forward. The method proposed in the paper firstly choose the exactly type and application components, then choose components further through component's functional match,...
This paper makes a brief research and analysis of current semantic annotation technology from different levels; and proposed a Chinese semantic annotation method which based on home appliance domain ontology according to the shortcomings of current semantic annotation prototypes. The method combined article level and lexical level annotation using SVM classification and NLP technology, which can improve...
This paper introduces an ontology mapping approach based on word and context similarity (WCONS) to find equivalence relation between concepts from two different ontologies, using Levenshtein distance and Tverskypsilas similarity model. The context of each concept is expanded to four kinds of facet contexts for context similarity computing, which are structure facet context, relation facet context,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.