Word concept model: a knowledge representation for dialogue agents

Information extraction is a key component in dialogue systems. Knowledge about the world as well as knowledge specific to each word should be used for robust semantic processing. An intelligent agent is necessary for a dialogue system when meanings are strictly defined by using a world state model. A layered concept structure is proposed to represent knowledge associated with each word in a "speech-friendly" way. By considering knowledge stored in the word concept model as well as knowledge base of the world model, meaning of a given sentence can be correctly identified. This paper describes the layered concept structure and how knowledge about words can be stored in this concept model.

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