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Analyzing Film Adaptation through Narrative Alignment
Tanzir Pial, Shahreen Salim, Charuta Pethe +2
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. Here we study thi…
GNAT: A General Narrative Alignment Tool
Tanzir Pial, Steven Skiena
Algorithmic sequence alignment identifies similar segments shared between pairs of documents, and is fundamental to many NLP tasks. But it is difficult to recognize similarities be…
STONYBOOK: A System and Resource for Large-Scale Analysis of Novels
Charuta Pethe, Allen Kim, Rajesh Prabhakar +2
Books have historically been the primary mechanism through which narratives are transmitted. We have developed a collection of resources for the large-scale analysis of novels, inc…
Hierarchies over Vector Space: Orienting Word and Graph Embeddings
Xingzhi Guo, Steven Skiena
Word and graph embeddings are widely used in deep learning applications. We present a data structure that captures inherent hierarchical properties from an unordered flat embedding…
Cleaning Dirty Books: Post-OCR Processing for Previously Scanned Texts
Allen Kim, Charuta Pethe, Naoya Inoue +1
Substantial amounts of work are required to clean large collections of digitized books for NLP analysis, both because of the presence of errors in the scanned text and the presence…
Chapter Captor: Text Segmentation in Novels
Charuta Pethe, Allen Kim, Steven Skiena
Books are typically segmented into chapters and sections, representing coherent subnarratives and topics. We investigate the task of predicting chapter boundaries, as a proxy for t…