University of Twente Student Theses


ArgueBot: Enabling debates through a hybrid retrieval-generation-based chatbot

Kulatska, I. (2019) ArgueBot: Enabling debates through a hybrid retrieval-generation-based chatbot.

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Abstract:The goal of this study is to develop a debate platform, the ArgueBot, that is able to maintain a meaningful debate with the user for various topics. The goal of the chatbot is to carry out human-like debates with the users. The Arguebot uses a hybrid model, combining retrieval- and generative-based models. The retrieval model uses cosine similarity to compare the user input with the argument candidates for a specific debate. The generative model is used to compensate for the limitations of the retrieval model that is restricted to the arguments stored in the database. The Arguebot utilizes Dialogflow, Flask, spaCy, and Machine Learning technologies within its architecture. The user tests and the survey are used to evaluate the chatbot’s performance. The user tests showed that there is a potential in the Arguebot, but it needs a better context understanding, a more accurate stance classifier, and a better generative model to become a more reliable debate partner.
Item Type:Essay (Master)
Findwise, Stockholm, Sweden
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Interaction Technology MSc (60030)
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