Ontogen : a knowledge-based approach to natural language generation

Authors
Leon, Ivan E.
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Other Contributors
Nirenburg, Sergei
McShane, Marjorie Joan, 1967-
Strzalkowski, Tomek
Issue Date
2020-08
Keywords
Cognitive science
Degree
MS
Terms of Use
Attribution-NonCommercial-NoDerivs 3.0 United States
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
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Abstract
A long-standing objective of artificial intelligence research has been to build collaborative agents that can communicate with humans via natural language. The fields of artificial intelligence and human-computer interaction have stake in building such agents that can communicate in a way that not only feels natural to us, but also opens the door to new ways in which humans can interact with agents beyond simple task automation. OntoGen is a Natural Language Generation (NLG) system that produces text from semantic meaning representations and generates grammatically correct and contextually relevant language. It is a rendering service for the OntoAgent cognitive architecture and provides the framework with the ability to generate language in a dialog context
Description
August 2020
School of Humanities, Arts, and Social Sciences
Department
Dept. of Cognitive Science
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
Access
CC BY-NC-ND. Users may download and share copies with attribution in accordance with a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. No commercial use or derivatives are permitted without the explicit approval of the author.