The Use of Paraphrase Identification in the Retrieval of Appropriate Responses for Script Based Conversational Agents
Jerome L. McClendon, Naja A. Mack, Larry F. Hodges · The Florida AI Research Society · 2014
This paper presents an approach to creating intelligent conversational agents that are capable of returning appropriate responses to natural language input. Our approach consists of using a supervised learning algorithm in combination with different NLP algorithms in training the system to identify paraphrases of the user’s question stored in a database. When tested on a data set consisting of questions and answers for a current conversational agent project, our approach returned an accuracy score of 79.15%, a precision score of 77.58%and a recall score of 78.01%.