TY - JOUR AU - Givon, Sharon AU - Wilson, Theresa PY - 2021/09/25 Y2 - 2024/03/29 TI - An Automatic Classification of Book Texts to User-Defined Tags JF - Proceedings of the International AAAI Conference on Web and Social Media JA - ICWSM VL - 2 IS - 1 SE - Poster Papers DO - 10.1609/icwsm.v2i1.18643 UR - https://ojs.aaai.org/index.php/ICWSM/article/view/18643 SP - 186-187 AB - <p>We describe work on automatically assigning labels to books using user-defined tags as the label set. Using supervised learning and exploring both binary and multiclass classification, we train and test classifiers on several sets of features, focusing on the size of the sets, part-of-speech classes and named entities. Results indicate that a binary classifier, trained and tested on a feature space that consists of a limited selection of parts of speech as well as all frequent named entities, achieves a classification precision of 81%, significantly outperforming a baseline which assigns the top-10 most popular tags to each book.</p> ER -