2013 IEEE 13th International Conference on Advanced Learning Technologies (ICALT) (2013)
July 15, 2013 to July 18, 2013
This paper presents a knowledge representation framework for natural language understanding. Here we propose an automated knowledge acquisition mechanism that mirrors information extraction in human-human interaction. This framework utilizes knowledge based automatic role labeling and automatic concept learning together with a conceptual structure that captures intent and context. The resulting framework is to be used to improve the agent's ability to engage in social interaction with humans.
Semantics, Knowledge representation, Knowledge based systems, Context, Natural languages, Educational institutions, Robustness
I. Fakinlede, V. Kumar and D. Wen, "Knowledge Representation for Context and Sentiment Analysis," 2013 IEEE 13th International Conference on Advanced Learning Technologies (ICALT), Beijing, China, 2013, pp. 493-494.