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SemAcom: A System for Modeling with Semantic Autocompletion
Citation key henning-agt-bizware-models-2012-2
Author Henning Agt
Title of Book Model Driven Engineering Languages and Systems - Demo Track, 15th International Conference, MODELS 2012, Innsbruck, Austria, Sept. 30 - Oct. 05, 2012
Year 2012
Abstract Autocompletion is a feature in various applications that assists users while typing into input fields. It predicts the user input based on background knowledge, rules and heuristics and is successfully used in mobile phones, web browsers, search engines and integrated development environments. We demonstrate SemAcom, a system for automatically suggesting related terms for domain-specific models. During the development of Ecore models with the Eclipse Modeling Framework SemAcom provides context-sensitive pop-up lists with related class names. The backbone of our system is a large-scale network of semantically related terms that was created automatically from a natural language dataset. The network contains probabilistic information how strong terms are related and is used to retrieve ranked lists of semantically related terms for a given set of input terms. That allows us to present the most relevant terms at the top of the list of suggestions.
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