Natural language processing (NLP) is an indispensable part of advancing the AI era, especially in the realm of the human-computer interface/interaction (HCI) for all state-of-the-art software applications. NLP enables interfaces between machines and humans allowing machines/computers/systems to understand human languages and engaging in dialogues. An intelligent chatbot development must incorporate NLP technologies to allow the understanding of users’ utterance and responding in understandable sentences in versatile scenarios. This research investigates the emerging technological trend of intelligent chatbot development. The systematic trend analysis is described in the research. First, patents related to intelligent chatbot domain are retrieved using a well-defined search query. The queries are derived from the knowledge ontology, which is extracted using text-mining algorithms - key term frequency analysis, clustering for sub-domain identification, and Latent Dirichlet Allocation (LDA) for topic modelling. Afterwards, the management and technology maps of a patent portfolio, such as patenting trends and technology function matrix, are extracted and drawn. The technology trend analysis also investigated the distributions of the relevant patent claims for specific industries.