Abstract：An Experimental Investigation of Semi-Automatic Generation of Concept Maps From Textbooks A concept map is a useful tool to organize and structure unstructured datain this casethe information contained in a textbookIn educationa concept map can be used to set learning goalsmonitor progress and visualize relationships between conceptsConstructing concept maps manually is a complex and time-consuming task which usually requires domain expertsAutomatic creation of concept maps from documents is called concept map miningIn this studywe explore various technical approaches to semi automate the process of generating a concept map from an e-textbookThe approach selected is to use the topics listed in the appendix as concepts and mine the relation between pairs of topics using natural language processing and machine learningLimitations of this approach and directions for future research are discussedRetrieval and IndexingThe conceptual map generation of automation can help students and educators to browse and understand the content of textbooks quicklythereby strengthening the retrieval and indexing abilityThe relationship between the relationship between the concept of the Nature Language ProcessingNLPand Machine Learning is semi-automatically generated from an electronic textbookNatural language processing is used to analyze the language structure in the text to determine the relative relationship between themes or conceptsand conceptsMachine learning is used to automatically identify and establish these relationships based on the information extracted from the text