The Application of AGNES Algorithm to Optimize Knowledge Base for Tourism Chatbot
Albert Verasius Dian Sano, Tanto Daud Imanuel, Mega Intanadias Calista, Hendro Nindito, Andreas Raharto Condrobimo · 2018
Most tourists have limited time and schedule when they are visiting a particular tourism area. One of the main issues faced by those tourists is that they can not make simple queries to search engines about, for example, which sites or places to visit optimally if we only have one day or two-day visit? Search engines are better and better in replying users' queries with relevant answers. However, search engines are not always able to respond queries suited to users' characteristics such as their styles, personalities, knowledge backgrounds, etc. Also, search engines are not as flexible as chatbots in enabling dialogical-communication-queries. This case study aims to respond aformentioned issue by applying hierarchical cluster analysis on a set of tourism sites around Malang city, Malang regency, and Batu city based on AGNES (Agglomerative Nesting) algorithm. The result, then, is fed into chatbot's knowledge base. This chatbot will assist tourists to get information on which possible sites they have to visit optimally if they are under limited vacancy-time constraints.