Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, and Krishnaram Kenthapadi
We present study navigator, an algorithmically-generated aid for enhancing the experience of studying from electronic textbooks. The study navigator for a section of the book consists of helpful concept references for understanding this section. Each concept reference is a pair consisting of a concept phrase explained elsewhere and the link to the section in which it has been explained. We propose a novel reader model for textbooks and an algorithm for generating the study navigator based on this model. We also present the results of an extensive user study that demonstrates the efficacy of the proposed system across textbooks on different subjects from different grades.
|Published in||International Conference on Information and Knowledge Management (CIKM)|
Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, and Krishnaram Kenthapadi. Study Navigator: An Algorithmically Generated Aid for Learning from Electronic Textbooks, Microsoft Research, 15 July 2013.