[PDF] Top 20 The Effect of Author Set Size in Authorship Attribution for Lithuanian
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The Effect of Author Set Size in Authorship Attribution for Lithuanian
... the Lithuanian language (the review in ˇ Zalkauskait˙e ...the Lithuanian texts is described in (Kapoˇci¯ut˙e-Dzikien˙e et ...normative Lithuanian language, few au- thors, and small training data; ... See full document
10
Authorship Attribution and Author Profiling of Lithuanian Literary Texts
... the authorship research were grad- ually replaced with e-mails (Abbasi and Chen, 2008), (de Vel et ...the Lithuanian language cov- ering other functional styles and language ... See full document
10
Tri Training for Authorship Attribution with Limited Training Data
... training set of the third ...we set the parameter u to a size of about 1% of the whole unlabeled set, which allows us to observe the effects of different number of ...labeled set to ... See full document
7
Authorship Attribution Using Text Distortion
... ter settings for each model. Then, the best models are applied to the test corpus. Table 3 presents the results of this experiment. As can be seen, the baseline models are the most effective ones using both character and ... See full document
12
Authorship Attribution with Topic Models
... vocabulary size of these two feature sets is larger than that of the stopword-only feature set, which suggests that DADT-P is more resilient to noise than Token ... See full document
42
Local Histograms of Character N grams for Authorship Attribution
... data set (recall that for this data set we consider 1, 3, 5, 10, and 50, randomly selected documents per ...training set sizes, which agree with results in Table 2 for the BC data ...data set ... See full document
11
Authorship Attribution of Micro Messages
... training size values (120 and 230). She also provided a set of experiments that studied the effect of joining several tweets into a sin- gle ... See full document
12
A Deep Context Grammatical Model For Authorship Attribution
... for authorship attribution by Feng et ...thorship attribution of literary texts, since sentence struc- ture features prominently in traditional literary analysis, and previous studies (Feng et ...in ... See full document
5
Influence of compression distance measures on Authorship Attribution
... Authorship attribution research can be broadly categorized in two ways. A set of features with machine learning algorithms and using compression ...for authorship attribution compared ... See full document
8
Leveraging Discourse Information Effectively for Authorship Attribution
... We have conducted an in-depth investigation of techniques that (i) featurize discourse information, and (ii) effectively integrate discourse features into the state-of-the-art character-bigram CNN classi- fier for AA. ... See full document
10
Authorship Attribution based on Data Compression for Telugu Text
... Authorship attribution research can be broadly categorized in two ways. Using a set of features and machine learning algorithms where as second way is by using compression ...training set of ... See full document
5
Lost in Translation: Authorship Attribution using Frame Semantics
... of authorship markers may be influenced by topics (Stein et ...the attribution methods in this ...thorship attribution have focused on the case of at- tributing texts among a small (N < 10) class ... See full document
6
Continuous N gram Representations for Authorship Attribution
... For all datasets, early stopping was used on the development sets and models trained with the Adam update rule (Kingma and Ba, 2015). Since none of the datasets have a standard develop- ment set, we randomly ... See full document
7
Short Text Authorship Attribution via Sequence Kernels, Markov Chains and Author Unmasking: An Investigation
... was set to 100 (with the highest average frequency in both texts) and the size of the chunks was set to 200 ...different- author curves for training the secondary ... See full document
10
Authorship Attribution and Verification with Many Authors and Limited Data
... per author (Argamon et ...authorial set’ (Burrows, ...specific author, the author attribu- tion task becomes much more ...candidate author is available, traditional approaches are less ... See full document
8
Authorship Attribution with Author aware Topic Models
... its size, topic-based methods were more strongly affected than SVM by the transi- tion from the 1,000 author subset to the full ...corpus size than SVM’s one-versus-all setup that uses one model per ... See full document
6
1. Authorship attribution using markov chain
... the authorship of new text, assuming that it was written by one of the known authors, we consider the probability of the text being generated by each of the transition ...Each author will thus be assigned ... See full document
7
Sparse Coding in Authorship Attribution for Polish Tweets
... The proposed method for the authorship attri- bution for Polish tweets expressed good perfor- mance for a large group of authors and large data set. It is based on the idea of an ap- plication of the ... See full document
9
Convolutional Neural Networks for Authorship Attribution of Short Texts
... We also wanted to explore how our method fares against the other methods when the problem becomes more difficult, i.e. when the number of authors increases or when the number of tweets per author decreases, as ... See full document
6
Enhancing Authorship Attribution By Utilizing Syntax Tree Profiles
... closed-class authorship attribution task, following the assumption that different authors have different writing styles in terms of the gram- mar structure that is used mostly ...an author has many ... See full document
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