Using Semantic Networks for Text Classification in Education: “Generating Tailored Questions for Students”
Badr Touis, Souhaib Aammou, Oussama Elwarraki, Jalal Lahiassi · Atlantis highlights in social sciences, education and humanities/Atlantis Highlights in Social Sciences, Education and Humanities · 2023
This paper discusses how semantic revolution can be used to represent textual data for text classification purposes.Text classification includes automatically classifying text data into predefined classes or categories, such as positive or negative sentiment, or articles categorized into different topics.The paper describes the method of using semantic networks to classify knowledge, including steps such as collecting and preprocessing text data sets, representing text data in the form of semantic networks, and training algorithms.Machine learning on a semantic network, which uses algorithms to classify new textual data and generate questions based on categorical output.The article also includes Python examples for some of the steps involved in the methodology.The paper highlights the power of semantic networks as a tool for knowledge representation and manipulation in AI and related fields.