We introduce the task of book structure labeling: segmenting and assigning a fixed category (such as TABLE OF CONTENTS, PREFACE, INDEX) to the document structure of printed books. We manually annotate the page-level structural categories for a large dataset totaling 294,816 pages in 1,055 books evenly sampled from 1750-1922, and present empirical results comparing the performance of several classes of models. The best-performing model, a bidirectional LSTM with rich features, achieves an overall accuracy of 95.8 and a class-balanced macro F-score of 71.4.
Allyship in academia is critical for creating inclusive communities that are welcoming to all students, but the perception of its benefits and challenges can vary depending on a number of factors. This session will explore perspectives of allyship in academia by bringing together a diverse group of faculty and students who can share a wide range of experiences and insights, and aims to facilitate a discussion among all attendees that leads to an exchange of ideas, the strengthening of our community, and progress toward our common goal of inclusion in computing. CCS CONCEPTS:• Social and professional topics~User characteristics • Social and professional topics~Informal education • Social and professional topics~Codes of ethics
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