Learning and Evaluating Character Representations in Novels

1 code implementation • Findings (ACL) 2022 • Naoya Inoue, Charuta Pethe, Allen Kim, Steven Skiena

We address the problem of learning fixed-length vector representations of characters in novels.

Word Embeddings

Analyzing Film Adaptation through Narrative Alignment

1 code implementation • 7 Nov 2023 • Tanzir Pial, Shahreen Salim, Charuta Pethe, Allen Kim, Steven Skiena

Novels are often adapted into feature films, but the differences between the two media usually require dropping sections of the source text from the movie script.

text similarity

STONYBOOK: A System and Resource for Large-Scale Analysis of Novels

no code implementations • 6 Nov 2023 • Charuta Pethe, Allen Kim, Rajesh Prabhakar, Tanzir Pial, Steven Skiena

Books have historically been the primary mechanism through which narratives are transmitted.

Cleaning Dirty Books: Post-OCR Processing for Previously Scanned Texts

1 code implementation • Findings (EMNLP) 2021 • Allen Kim, Charuta Pethe, Naoya Inoue, Steve Skiena

We present methods to handle these errors, evaluated on a collection of 19, 347 texts from the Project Gutenberg dataset and 96, 635 texts from the HathiTrust Library.

Optical Character Recognition Optical Character Recognition (OCR)

Chapter Captor: Text Segmentation in Novels

1 code implementation • EMNLP 2020 • Charuta Pethe, Allen Kim, Steven Skiena

Books are typically segmented into chapters and sections, representing coherent subnarratives and topics.

Segmentation Text Segmentation

What time is it? Temporal Analysis of Novels

1 code implementation • EMNLP 2020 • Allen Kim, Charuta Pethe, Steven Skiena

Recognizing the flow of time in a story is a crucial aspect of understanding it.

Descriptive