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This paper presents a novel Semantic-Based Conversational Agent (SCA). Traditional conversational agents (CA) interpret scripts consisting of structural patterns of sentences, which take no consideration of semantic content. The script writer must therefore anticipate the many variations of input the user may respond with during dialogue. This is evidently a high maintenance task. Furthermore, different...
This paper presents a novel framework for constructing a Semantic-Based Conversational Agent (SCAF). Traditional conversational agents (CA) interpret scripts using structural patterns of sentences, which require the script writer to consider every possible permutation that a user may send as input to the CA. This is a time-consuming process, which takes no consideration of semantic content, working...
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