Visualizing Textbook Concepts: Beyond Word Co-occurrences

• Published in: Computational Linguistics and Intelligent Text Processing Vol. 10761; pp. 363 - 376
• Main Authors: Sastry, Chandramouli Shama, Jagaluru, Darshan Siddesh, Mahesh, Kavi
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2018; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Concept extraction; Concept relations; Term co-occurrences; Textbook visualization; Transitive closure
• ISBN: 3319771124; 9783319771120
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-77113-7_29

In this paper, we present a simple and elegant algorithm to extract and visualize various concept relationships present in sections of a textbook. This can be easily extended to develop visualizations of entire chapters or textbooks, thereby opening up opportunities for developing a range of visual applications for e-learning and education in general. Our algorithm creates visualizations by mining relationships between concepts present in a text by applying the idea of transitive closure rather than merely counting co-occurrences of terms. It does not require any thesaurus or ontology of concepts. We applied the algorithm to two textbooks - Theory of Computation and Machine Learning - to extract and visualize concept relationships from their sections. Our findings show that the algorithm is capable of capturing deep-set relationships between concepts which could not have been found by using a term co-occurrence approach.