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Data Mining for Improving Textbooks (invited paper)

Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, and Krishnaram Kenthapadi


We present our early explorations into developing a data mining based approach for enhancing the quality of textbooks. We describe a diagnostic tool to algorithmically identify deficient sections in textbooks. We also discuss techniques for algorithmically augmenting textbook sections with links to selective content mined from the Web. Our evaluation, employing widely-used textbooks from India, indicates that developing technological approaches to help improve textbooks holds promise.


Publication typeInproceedings
Published inSIGKDD Explorations Newsletter
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