Abstract
In the proposed work is performed a text classification for a chatbot
application used by a company working in assistance services of
automatic warehouses. industries. Specifically, text mining technique is
adopted for the classification of questions and answers. Business
Process Modeling Notation (BPMN) models describe the passage from
“AS-IS” to “TO BE” in the context of the analyzed
industry, by focusing the attention mainly on customer and technical
support services where chatbot is adopted. A two-step process model is
used to connect technological improvements and relationship marketing in
chatbot assistance: the first step provides the hierarchical clustering
able to classify questions and answers through Latent Dirichlet
Allocation -LDA- algorithm, and the second one executes the Tag Cloud
representing the visual representation of more frequent words contained
in the experimental dataset. Tag cloud is used to show the critical
issues that customers find in the usage of the proposed service. By
considering an initial dataset, 24 hierarchical clusters are found
representing the preliminary combination of the couple’s
question-answer. The proposed approach is suitable to automatically
construct a combination of chatbot questions and appropriate answers in
intelligent systems.