Papers by Allen Kim
Chapter Ordering in Novels (2022.emnlp-main)
Copied to clipboard
| Challenge: | a major challenge in research on long-form narrative texts is the cost of annotation . authors propose a new task that reconstructs the original order of chapters in novels without the need for human annotation. |
| Approach: | They propose a task that reconstructs the original order of chapters in novels given a random permutation of the text. |
| Outcome: | The proposed task yields a Spearman correlation of 0.59 on the novel and challenging task, substantially above baseline. |
Chapter Captor: Text Segmentation in Novels (2020.emnlp-main)
Copied to clipboard
| Challenge: | Using a hybrid approach, we identify chapter boundaries in novels . chapter boundaries are typically denoted by formatting conventions such as page breaks, white-space, chapter numbers, and titles. |
| Approach: | They build a project Gutenberg data set of 9,126 English novels to analyze chapter boundaries . they use neural inference and rule matching to recognize chapter title headers . |
| Outcome: | The proposed method achieves an F1 score of 0.77 on the segmentation task . the annotated data reveal interesting historical trends in the chapter structure of novels . |
Cleaning Dirty Books: Post-OCR Processing for Previously Scanned Texts (2021.findings-emnlp)
Copied to clipboard
| Challenge: | a large amount of work is required to clean digitized books for NLP analysis because of errors in the scanned text and duplicate volumes in the corpora. |
| Approach: | They propose methods to handle optical character recognition errors in scanned texts . they identify the canonical version for each of 17,136 repeatedly-scanned books . |
| Outcome: | The proposed method corrects over six times as many errors as it introduces, the authors show . the authors evaluate a collection of 19,347 texts from the Gutenberg dataset and 96,635 from the HathiTrust Library . |
What time is it? Temporal Analysis of Novels (2020.emnlp-main)
Copied to clipboard
| Challenge: | a novel based on the flow of time provides a framework for understanding the text . a computational approach to annotate a book's lines with wall clock times is needed to understand the flow through time. |
| Approach: | They propose to annotate each line of a book with wall clock times . they use a data set of hourly time phrases from 52,183 fictional books . |
| Outcome: | The proposed method improves upon baselines by over two hours and can partition a book into segments that correspond to a particular time-of-day. |
Analyzing Film Adaptation through Narrative Alignment (2023.emnlp-main)
Copied to clipboard
| Challenge: | a new study examines the book-to-film adaptation process by examining the differences between the two media . novel adaptations often require dropping sections of the source text from the movie script . |
| Approach: | They use a Smith-Waterman local alignment algorithm to quantify text similarity between scenes and book units. |
| Outcome: | The proposed method reveals that novel adaptations often require dropping parts of the source text from the movie script. |
Learning and Evaluating Character Representations in Novels (2022.findings-acl)
Copied to clipboard
| Challenge: | Recent advances in word embeddings have proven successful in learning entity representations from short texts but do not capture full book-level information. |
| Approach: | They propose two novel ways to learn fixed-length vector representations of characters from novels . they use graph neural network-based embeddings from a full corpus-based character network . |
| Outcome: | The proposed methods outperform text-based embeddings in four tasks. |