Intent Arabic text categorisation based on different machine learning and term frequency
Mohammad Fadhil Mahdi, Mahmoud Shuker Mahmoud · IET Networks · 2022
Abstract The complexity of Internet network configurations has made managing networks a complicated undertaking. Intent‐Based Networking (IBN) is a potential solution to this issue. In contrast to conventional networks, where a concrete description of the settings typically conveys a network administrator's goal kept on each device, an administrator's intent in an IBN is articulated prescriptively and abstractly as what he intends to do. Based on reactive settings that convey the administrator's intention, a technique that enables an administrator to automatically alter network configuration in response to changes in the external environment is provided. This research will discuss automatic network management techniques based on term frequency and machine learning models (SVM, NB, DT, and KNN). The tests were conducted, and the outcomes showed that the SVM produced accurate results (86.324%). As a result, the SVM in the proposed model is very acceptable.