Intent Expression Through Natural Language Processing in an Enterprise Network
Elie El-Rif, Aris Leivadeas, Matthias Falkner · 2023
The unprecedented expansion of network communications and the addition of new applications and services have made the network configuration a riddle for network engineers. At the same time, the daily interaction of the users with various network applications and the heterogeneous requirements they impose, necessitates a more direct communication between these two entities. Intent Based Networking (IBN) is a new technology that enables this by automating the network configuration, while allowing the users to directly interact with the network. The latter can be established through a natural language form, letting the users to freely express their high-level network requirements via a normal conversational approach. To this end, in this paper, we introduce ETS-Chatbot by extending the functionalities of a chatbot in order to be used in an IBN context. We position our work in an enterprise environment and we try to capture the high-level intent and map it into a model that can be understood by the network. The obtained results reveal that our framework can accurately classify the intent of a user with high precision, giving a strategic advantage to the enterprise.