2020/11/20 by Shivam Pal, Pal, Shivam, Vipul Arora +3
Computer Science · #Advanced Text Analysis Techniques #Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Machine Learning (cs.LG) #Text and Document Classification Technologies #Topic Modeling
paper · pdf · doi:10.48550/arxiv.2011.10337
openalex publication_date 2020/11/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A prerequisite is anything that you need to know or understand first before attempting to learn or understand something new. In the current work, we present a method of finding prerequisite relations between concepts using related textbooks. Previous researchers have focused on finding these relations using Wikipedia link structure through unsupervised and supervised learning approaches. In the current work, we have proposed two methods, one is statistical method and another is learning-based method. We mine the rich and structured knowledge available in the textbooks to find the content for those concepts and the order in which they are discussed. Using this information, proposed statistical method estimates explicit as well as implicit prerequisite relations between concepts. During experiments, we have found performance of proposed statistical method is better than the popular RefD method, which uses Wikipedia link structure. And proposed learning-based method has shown a significant increase in the efficiency of supervised learning method when compared with graph and text-based learning-based approaches.