[PDF] Top 20 Cross Language Authorship Attribution
Has 10000 "Cross Language Authorship Attribution" found on our website. Below are the top 20 most common "Cross Language Authorship Attribution".
Cross Language Authorship Attribution
... According to psychological studies (Dunn et al., 1989), most of the people could be roughly divided into visual, au- dial and kinesthetic learners, i.e. those who better perceive visual, audial or kinesthetic information ... See full document
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Authorship Attribution with Author aware Topic Models
... al., 2006). These datasets represent realistic scenar- ios of AA of user-generated texts with many can- didate authors. For example, Chaski (2005) notes a case where an employee who was terminated for sending a racist ... See full document
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Authorship Attribution with Convolutional Neural Networks and POS Eliding
... what remarkable accuracy well above chance. Al- though the performance of our particular system does not justify a use in legal or forensic settings, as more than 85% of predictions were still incor- rect, the public ... See full document
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Convolutional Neural Networks for Authorship Attribution of Short Texts
... many authorship attribution systems (Stamatatos, 2009; Schwartz et ...for authorship attribution (Rhodes, ...character language model that gives a set of next character probabilities ... See full document
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Modality Specific Meta Features for Authorship Attribution in Web Forum Posts
... In another interesting recent work on AA, Prob- abilistic Context-Free Grammars (PCFGs) were proposed for AA (Raghavan et al., 2010). The number of authors in the evaluation data sets was rather small (3 to 6) but it ... See full document
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1. Authorship attribution using markov chain
... using cross validation. In cross validation, we considered 4 samples of each blogger, so in all we have 20 ...of authorship is done for the one text which was not used in computation of ... See full document
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Sparse Coding in Authorship Attribution for Polish Tweets
... the cross-domain model scenario, see Table 3 and Table 4, show a different ...second cross- domain experiment, all the results decreased, but only ... See full document
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A Deep Context Grammatical Model For Authorship Attribution
... Stamatatos (2009) describes a number of other shortcom- ings with the syntactic approach, including the language dependence of the parsing/tagging tools required in order to prepare the source text, and the ... See full document
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Literary authorship attribution with phrase structure fragments
... text with the highest probability. There is also work that looks at syntax on a more shallow level, such as Hirst and Feiguina (2007), who work with par- tial parses; Wiersma et al. (2011) looked at n-grams of ... See full document
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Continuous N gram Representations for Authorship Attribution
... and run experiments with 10-fold cross-validation. CCAT10 (Stamatatos, 2008). This dataset is a subset of Reuters Corpus Volume 1 (RCV1) (Rose et al., 2002) and consists of newswire stories by 10 authors labelled ... See full document
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An Off the shelf Approach to Authorship Attribution
... approaches, authorship attribution has been studied with a wide range of different ...natural language processing (Stamatatos et ...for authorship studies, for instance, (Holmes and Crofts, ... See full document
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Maximal Repeats Enhance Substring-based Authorship Attribution
... This article tackles the Authorship Attri- bution task according to the language in- dependence issue. We propose an alterna- tive of variable length character n-grams features in supervised methods: ... See full document
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Authorship Attribution and Verification with Many Authors and Limited Data
... ship attribution starts from unrealistic assumptions about numbers of authors and amount of training data ...in authorship attribution on twenty authors in a corpus of Usenet newsgroups on a variety ... See full document
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Authorship Attribution and Author Profiling of Lithuanian Literary Texts
... Polish language were performed with the literary texts of 2 au- thors using the feed-forward multilayer Percep- tron method (with one or two hidden layers) and the sigmoid activation function trained by the ... See full document
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Using the Complexity of the Distribution of Lexical Elements as a Feature in Authorship Attribution
... It has been shown that the addition of Kolmogorov complexity measures of lexical features increases the accuracy of a feature-based author attribution SVM model by 5.2%-11.8%. In fact the Kolmogorov complexity ... See full document
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Assessing the Stylistic Properties of Neurally Generated Text in Authorship Attribution
... In his landmark paper ‘Computing Machinery and Intelligence‘, Turing (1950) quoted Jefferson’s ‘The Mind of Mechanical Man’ (1949): ‘Not until a machine can write a sonnet or compose a con- certo because of thoughts and ... See full document
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Optimum Parameter Selection for K L D Based Authorship Attribution in Gujarati
... present in the corpus. Accuracy is then calculated in two ways: by finding the total number of articles attributed correctly irrespective of the authors (mi- cro average) and by finding the accuracy for each author ... See full document
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Authorship Attribution Using Probabilistic Context Free Grammars
... writing style at the syntactic level, it may not accu- rately capture lexical information. Since both syn- tactic and lexical information is presumably useful in capturing the author’s overall writing style, we also ... See full document
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Lost in Translation: Authorship Attribution using Frame Semantics
... general authorship attribution problem, the specific problem of attributing trans- lated texts to their original author has received little ...proper attribution to the original author will be very ... See full document
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The Effect of Author Set Size in Authorship Attribution for Lithuanian
... Lithuanian language (the review in ˇ Zalkauskait˙e ...Lithuanian language, few au- thors, and small training data; therefore findings are not robust to make the generalizations about which method is the ... See full document
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