Mining videos from the web for electronic textbooks

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Abstract

We propose a system for mining videos from the web for supplementing the content of electronic textbooks in order to enhance their utility. Textbooks are generally organized into sections such that each section explains very few concepts and every concept is primarily explained in one section. Building upon these principles from the education literature and drawing upon the theory of Formal Concept Analysis, we define the focus of a section in terms of a few indicia, which themselves are combinations of concept phrases uniquely present in the section. We identify videos relevant for a section by ensuring that at least one of the indicia for the section is present in the video and measuring the extent to which the video contains the concept phrases occurring in different indicia for the section. Our user study employing two corpora of textbooks on different subjects from two countries demonstrate that our system is able to find useful videos, relevant to individual sections. © 2014 Springer International Publishing.

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APA

Agrawal, R., Christoforaki, M., Gollapudi, S., Kannan, A., Kenthapadi, K., & Swaminathan, A. (2014). Mining videos from the web for electronic textbooks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8478 LNAI, pp. 219–234). Springer Verlag. https://doi.org/10.1007/978-3-319-07248-7_16

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