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Showing 1 to 12 of 12 for “"Authorship attribution"”.
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Authorship attribution using lexical attraction
Thesis (M.Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.
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Authorship Attribution on the Enron Email Corpus
In this paper I present authorship attribution on an email corpus. The source I used was the Enron Email Corpus (Cohen, 2009). By reformatting these emails, four test sets were categorized based on the length of each email: Tiny (≤ 99 characters), Small (100 to 500 characters), Medium (501 to 999 …
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Authorship Attribution Through Words Surrounding Named Entities
In text analysis, authorship attribution occurs in a variety of ways. The field of computational linguistics becomes more important as the need of authorship attribution and text analysis becomes more widespread. For this research, pre-existing authorship attribution software, Java Graphical …
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Best Practices in Authorship Attribution of English Essays
… is used to determine the best practices in authorship attribution for English essays, specifically examining the methods available in JGAAP version 4.3 and their performance on problem A of the AAAC corpus. Best practices were determined by ranking the logistic regression coefficient …
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Self-attentive generative adversarial network-based authorship attribution in historical texts
Authorship Attribution is the task of identifying the author of an unknown text. Given the large number of disputed texts and widespread use of pen names in humanities, especially in historical and literary texts, this study aims to follow a deep-learning-based approach to perform authorship …
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Benchmarking authorship attribution techniques using over a thousand books by fifty Victorian era novelists
Authorship attribution (AA) is the process of identifying the author of a given text and from the machine learning perspective, it can be seen as a classification problem. In the literature, there are a lot of classification methods for which feature extraction techniques are conducted. In this …
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The Open Class Authorship Attribution Problem: A Comparison of Mixture-of-Experts Methods within the JGAAP Framework
… evaluate, and compare methods of open class attribution that utilize multiple unique closed class attributions in a voting framework. By applying statistical techniques to the proportion of closed class attributions indicating individual candidate authors, we seek to determine if the author …
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Language technologies for understanding law, politics, and public policy
… these document collections. First, we present an authorship attribution model on unsigned U.S. Supreme Court opinions, offering insights into the authorship of important cases and the dynamics of Supreme Court decision-making. Second, we apply software engineering metrics to analyze the complexity …
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The multifaceted measurement of the individual through language
… psychometric approach via language in realms of authorship attribution and value measurement. In 2 of the 3 studies, language analytic techniques are used to measure consistencies within the individual that can be capitalized upon in order to determine authorial identities. In the third study, …
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Domain Adaptation using Deep Adversarial Models
… natural language processing and specifically authorship attribution; however, our approach is not restricted to a specific field or data type, and a variety of tasks are explored. We investigate an unsupervised multiple-domain adaptation scenario with multiple labeled source data sets and …