Goal— oriented conversational bot for employment domain
Paweł Drozda
UWMTomasz Żmijewski
Maciej Osowski
Aleksandra Krasnodębska
Arkadiusz Talun
Abstract
This paper focuses of the implementation of the goal – oriented chatbot in order to prepare virtual resumes of candidates for job position. In particular the study was devoted to testing the feasibility of using Deep Q Networks (DQN) to prepare an effective chatbot conversation flow with the final system user. The results of the research confirmed that the use of the DQN model in the training of the conversational system allowed to increase the level of success, measured as the acceptance of the resume by the recruiter and the finalization of the conversation with the bot. The success rate increased from 10% to 64% in experimental environment and from 15% to 45% in production environment. Moreover, DQN model allowed the conversation to be shortened by an average of 4 questions from 11 to 7.
Keywords:
chatbot, Deep Q Network (DQN), goal – oriented bot, Natural Language Processing (NLP)Supporting Agencies
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