Since the mid-20th century, when artificial intelligence began to emerge as an academic field, a variety of machine learning techniques have been developed. While researchers developed the field, they had difficulties putting these machine learning concepts into practice. Now that the capabilities of computers in our generation have become much more powerful, what had been researched upon has started to be applied to our everyday lives in order to improve our living standards. Even though we are still at the beginning of the age of artificial intelligence and its applications are still far from perfection, they have already reached the point where they are useful. The paper seeks to prove the utility of artificial intelligence in the form of a chatbot, an automated text generator, using a machine learning technique called Long Short-Term Memory, while also analyzing behavioral differences of chatbots learning from datasets consisting of different levels of vocabulary. Conclusively, the results come out to prove the utility of chatbots and behavioral differences to a certain extent.
Shimizu, Sota, "Analyzing Behavioral Differences of LSTM Chatbots Learning from Different Levels of Vocabulary Sets" (2019). Senior Independent Study Theses. Paper 8401.
Machine Learning, Artificial Intelligence, Chatbot, LSTM, Sequence to Sequence
Bachelor of Arts
Senior Independent Study Thesis
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