DI-2021 @ KDD 2021: Collins-Thompson Talk Recording
Recording of invited talk 2/6 in Document Intelligence Workshop @ KDD2021 given by Kevyn Collins-Thompson, Associate Professor of Information and Computer Science at University of Michigan.
Title: Enhancing Document Representations Using Analysis of Content Difficulty: Models, Applications, and Insights https://youtu.be/5NekLenxPDc
Abstract: This talk will discuss how enhancing document representations with analysis of language complexity and difficulty can lead to a surprisingly wide range of new applications and insights into how people interact with content in both business and educational settings. Analyzing the difficulty of language has a history going back to the ancient Greeks, who understood that a legal argument or analysis was of little persuasive value if its audience could not understand it. Classic 20th century text readability formulas, such as Flesch-Kincaid, combined statistics like average sentence length and average number of syllables in a text to estimate its readability. However, the limitations of these simple traditional measures, including lack of flexibility for new tasks and populations and robustness for non-traditional documents, has led to a new branch of natural language processing research that has developed richer, more effective data-driven computational models of reading comprehension and text complexity [1]. First I’ll give a brief summary of recent advances in modeling content difficulty and complexity, including my own work on statistical models of readability and deep learning for predicting the informativeness of text. Then I’ll give some examples of insights that derive from applying these methods for creating richer, difficulty-based document representations, using empirical methods ranging from in-lab user studies with eyetracking, to large-scale commercial search interaction data over millions of sessions and Web pages. Finally, I’ll touch on some on-going work and potential future directions in educational scenarios for understanding and supporting learners, toward the goal of high quality, personalized learning experiences.
Program committee (alphabetical): Doug Burdick, Dave Lewis, Yijuan Lu, Hamid Motahari, Sandeep Tata Chair: Benjamin Han
Originally posted on LinkedIn.