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Diederich, Joachim; Kindermann, Jörg; Leopold, Edda; Paaß, Gerhard

doi:10.1023/a:1023824908771

Cited by 224 publications

(12 citation statements)

References 31 publications

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“…The average word length was determined to be 6241 letters and it was seen that the words up to 7 letters constituted 69.11% of the total corpus. Demirci, S. (2014)…”

Section: Statistical Methods (Probability Calculations)mentioning

confidence: 99%

“…Destek vektör makinesi Türkçeye uygulanan üslup analizi çalışmalarında yaygın olarak kullanılan algoritmalardan biridir. Üslup analizi çalışmalarında SVM'nin ayırt edici avantajı binlerce farklı özelliği işleyebilme yeteneğidir (Diederich, Kindermann, Leopold ve Paass, 2003). Türkoğlu ve diğerlerinin (2007) 2.000'i aşkın özellik vektörü ile yaptığı çalışmada SVM; naive Bayes, rastgele orman ve çok katmanlı algılayıcı algoritmaları arasında en yüksek başarı düzeyine ulaşan makine ile öğrenme algoritması olmuştur.…”

Section: Sınıflandırma Yaklaşımlarıunclassified

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Türkçe Metinler Üzerine Yapılan Sayısal Üslup Araştırmalarını İnceleyen ve Benim Adım Kırmızı Çevirilerinin Aslına Olan Sadakatini Ölçen Bir Çalışma (A Survey of Stylometry Research on Turkish Texts and A Study on Quantification of Loyalty for Translations of My Name is Red)

Çalışkan¹,

Can²

2018

tkd

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ÖzBu makalede bilişimin beşerî bilimlerdeki önemli bir uygulaması olan sayısal üslup analizi yönteminin tanıtılması hedeflenmiş ve çevirilerin aslına sadakatini ölçen özgün bir araştırma sunulmuştur. Sayısal üslup analizi, bilgi ve belge yönetiminde çeşitli sınıflama işlemlerini gerçekleştiren ve edebiyat araştırmalarında yakın okuma sırasında görülmesi mümkün olmayan gözlemleri sağlayan yaklaşımlardan oluşmaktadır. Makalede, öncelikle Türkçe metinler üzerinde çalışmak isteyen araştırmacılar için, üslup analizinin Türkçeye nasıl uyarlanacağı anlatılmış ve bu konuda Türkçe metinler üzerinde yapılan çalışmaları inceleyen kapsamlı bir kaynak taraması sunulmuştur. Üslup analizinin uygulama amaçları örneklerle incelenmiş, ön işleme ve öznitelik çıkarımı, sınıflandırma yaklaşımları, başarı düzeyi değerlendirmesi ve yardımcı bilişim araçları konularına yer verilmiştir. Orhan Pamuk'un Benim Adım Kırmızı isimli romanı ve çevirilerindeki üslup uyumuna ilişkin sunulan özgün araştırma, roman kahramanlarının temel bileşenler düzlemindeki dağılımlarını inceleyen yeni bir yaklaşım kullanmaktadır. İstatistiksel olarak kayda değer olan gözlemler yazar üslubunun çevirilerde korunduğunu gösteren niteliktedir. Anahtar Sözcükler: Üslup analizi; metin madenciliği; yazar doğrulama; yazar ataması; metin sınıflandırma. AbstractIn this article an important problem of digital humanities, stylometry, is introduced and a novel study on quantification of translation loyalty is presented. Stylometry involves approaches that perform various classification tasks in information and document management and provides observations in literary analyses that cannot be obtained by close reading. A comprehensive 252 Araştırma Makaleleri / Research Articles Çalışkan ve Can survey of related studies and ways of adapting them to Turkish are presented for researchers who want to work on Turkish texts. In this context, the purpose of stylistic analysis, pre-processing, feature extraction and classification approaches, performance measures and available software tools are provided. Our new study on Orhan Pamuk's novel My Name is Red quantifies the consistency of translations with the original work and uses a new approach that examines the distributions of novel protagonists on the principal components analysis plane. Statistically significant observations show that the writer style is preserved in translations.

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“…The average word length was determined to be 6241 letters and it was seen that the words up to 7 letters constituted 69.11% of the total corpus. Demirci, S. (2014)…”

Section: Statistical Methods (Probability Calculations)mentioning

confidence: 99%

Section: Sınıflandırma Yaklaşımlarıunclassified

Türkçe Metinler Üzerine Yapılan Sayısal Üslup Araştırmalarını İnceleyen ve Benim Adım Kırmızı Çevirilerinin Aslına Olan Sadakatini Ölçen Bir Çalışma (A Survey of Stylometry Research on Turkish Texts and A Study on Quantification of Loyalty for Translations of My Name is Red)

Çalışkan¹,

Can²

2018

tkd

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“…Zhao and Zobel 2005) and above all support-vector machine (SVM) techniques (e.g. Diederich et al 2003;Koppel and Schler 2004). Th e SVM technique is still probably the most popular in contemporary stylometry although deep-learning methods seem poised to overtake it (see , e.g.…”

Section: Support-vector Machinesmentioning

confidence: 99%

Versification and Authorship Attribution

Plecháč¹,

Šeļa²

2021

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The technique known as contemporary stylometry uses different methods, including machine learning, to discover a poem’s author based on features like the frequencies of words and character n-grams. However, there is one potential textual fingerprint stylometry tends to ignore: versification, or the very making of language into verse. Using poetic texts in three different languages (Czech, German, and Spanish), Petr Plecháč asks whether versification features like rhythm patterns and types of rhyme can help determine authorship. He then tests its findings on two unsolved literary mysteries. In the first, Plecháč distinguishes the parts of the Elizabethan verse play The Two Noble Kinsmen written by William Shakespeare from those written by his coauthor, John Fletcher. In the second, he seeks to solve a case of suspected forgery: how authentic was a group of poems first published as the work of the nineteenth-century Russian author Gavriil Stepanovich Batenkov? This book of poetic investigation should appeal to literary sleuths the world over.

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“…Within the natural language processing community, many popular techniques exist to solve such a problem, including Naive Bayes [5] and support vector machines [6]. Although these techniques have limitations, such as ignoring word order, they proved to be good enough for classification tasks such as sentiment analysis [7] or authorship attribution [8].…”

Section: Convolutional Neural Network For Nlpmentioning

confidence: 99%

Predicting How to Test Requirements: An Automated Approach

Winkler

Grönberg

Vogelsang

2019

2019 IEEE 27th International Requirements Engineering Conference (RE)

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Context] An important task in requirements engineering is to identify and determine how to verify a requirement (e.g., by manual review, testing, or simulation; also called potential verification method). This information is required to effectively create test cases and verification plans for requirements. [Objective] In this paper, we propose an automatic approach to classify natural language requirements with respect to their potential verification methods (PVM).[Method] Our approach uses a convolutional neural network architecture to implement a multiclass and multilabel classifier that assigns probabilities to a predefined set of six possible verification methods, which we derived from an industrial guideline. Additionally, we implemented a backtracing approach to analyze and visualize the reasons for the network's decisions.[Results] In a 10-fold cross validation on a set of about 27,000 industrial requirements, our approach achieved a macro averaged F 1 score of 0.79 across all labels. For the classification into test or non-test, the approach achieves an even higher F 1 score of 0.94. [Conclusions] The results show that our approach might help to increase the quality of requirements specifications with respect to the PVM attribute and guide engineers in effectively deriving test cases and verification plans.

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Cited by 224 publications

References 31 publications

Türkçe Metinler Üzerine Yapılan Sayısal Üslup Araştırmalarını İnceleyen ve Benim Adım Kırmızı Çevirilerinin Aslına Olan Sadakatini Ölçen Bir Çalışma (A Survey of Stylometry Research on Turkish Texts and A Study on Quantification of Loyalty for Translations of My Name is Red)

Türkçe Metinler Üzerine Yapılan Sayısal Üslup Araştırmalarını İnceleyen ve Benim Adım Kırmızı Çevirilerinin Aslına Olan Sadakatini Ölçen Bir Çalışma (A Survey of Stylometry Research on Turkish Texts and A Study on Quantification of Loyalty for Translations of My Name is Red)

Versification and Authorship Attribution

Predicting How to Test Requirements: An Automated Approach

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