Abstract
A sudden interest in chatbots occurred in 2016 due to the advancements in machine learning and artificial intelligence technologies. The increase of mobile messaging applications and the introduction of chatbot development frameworks allowed researchers to explore different paradigms for building chatbots. A major issue related to the user experience with chatbots was detected. Users with different personalities, preferences, and needs receive the same responses when they interact with a particular chatbot. This can create unpleasant experiences towards certain user groups. There were multiple efforts to create personalized chatbots in order to overcome such experiences. In this paper, a systematic review for personalized chatbots is conducted to investigate the attempts of building psychologically-driven personalized chatbots. Accordingly, we propose a generic framework for building character-based chatbots using the principles of Character Computing based on psychological theorizing. Our goal is to allow users to create their individual chatbot characters by selecting their preferred character traits. To this end, we introduce a retrieval-based approach for implementing our proposed framework.
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El Hefny, W., El Bolock, A., Herbert, C., Abdennadher, S. (2020). Towards a Generic Framework for Character-Based Chatbots. In: De La Prieta, F., et al. Highlights in Practical Applications of Agents, Multi-Agent Systems, and Trust-worthiness. The PAAMS Collection. PAAMS 2020. Communications in Computer and Information Science, vol 1233. Springer, Cham. https://doi.org/10.1007/978-3-030-51999-5_8
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