Today the importance of having a healthy, nutritious diet is greater than ever. One of the main tools in achieving this goal is an efficient way to record the meals one has consumed throughout the day. This diploma thesis gives a brief overview of chatbots in general, but focuses on implementing the logic for a domain specific chatbot. The domain is determined by a database containing almost one thousand foods. The goal is to gather enough information from the user to identify the foods consumed during a particular meal. We use natural language processing (NLP) methods such as lemmatisation, cosine distance, string matching and levenshtein distance. The chatbot is also capable of forming systematical questions when the speech input is incomplete or unclear. The prototype of the chatbot is available as a Java Swing Application for personal computers.
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