Files in this item



application/pdfMalic543.pdf (1MB)
(no description provided)PDF


application/octet-streamMalic543.epub (438kB)
(no description provided)Unknown


Title:Analyzing historians' perspectives using semantic measures
Author(s):Malic, Vincent Quirante
Subject(s):semantic relatedness
text mining
knowledge mining
vector space model
Abstract:Historians create structure in our collective understanding of past events. When writing narrative history, they establish connections between significant events, the contexts in which these events occurred, and the people who participated in them. Most of the knowledge created by historians still exists in the form of unstructured texts. This poster presents an exploration of the applicability of the concept of semantic relatedness to historiographical research. Computational methods are applied on texts about the history of the Roman Empire to identify named entities and build word-word relatedness matrices. These matrices are then analyzed to reveal larger thematic structures that characterize a particular historian's view of historical events. This analysis demonstrates the value of semantic relatedness for the unsupervised detection of common themes and unusual outliers in the narrative texts historians have created to store our collective knowledge of the past.
Issue Date:2016-03-15
Citation Info:NA
Series/Report:IConference 2016 Proceedings
Genre:Conference Poster
Rights Information:Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.
Date Available in IDEALS:2016-03-08

This item appears in the following Collection(s)

Item Statistics