Data Set Used
Segmenting text into semantically coherent fragments improves readability of text and facilitates tasks like text summariza-tion and passage retrieval. In this paper , we present a novel unsupervised algorithm for linear text segmentation (TS) that exploits word embeddings and a measure of semantic relatedness of short texts to construct a semantic… (More)
Introduction Humanities scholars have experimented with the potential of different text mining techniques for exploring large corpora, from cooccurrencebased methods to sequencelabeling algorithms (e.g. Named entity recognition). LDA topic modeling (Blei et al., 2003) has become one of the most employed approaches (Meeks and Weingart, 2012). Scholars… (More)
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