This article summarizes the research on computational methods to detect academic
plagiarism by systematically reviewing 239 research papers published between 2013 and …

The education sector has benefited enormously through integrating digital technology driven
tools and platforms. In recent years, artificial intelligence based methods are being …

The vast majority of previous studies in authorship attribution assume the existence of
documents (or parts of documents) labeled by authorship to be used as training instances in …

В статті розглянуто поняття плагіату, самоплагіату та їх основні види. Приведено
класифікацію інструментів автоматичного відстеження плагіату у текстових документах …

Plagiarism is a rising issue in academics as increasing resources constantly, and it plays a
high impact on student's performance and quality of education. Several studies have been …

Detecting plagiarism in documents is a well-established task in natural language processing
(NLP). Broadly, plagiarism detection is categorized into two types (1) intrinsic: to check the …

Identifying academic plagiarism is a pressing problem, among others, for research
institutions, publishers, and funding organizations. Detection approaches proposed so far …

In the realm of text analysis, intrinsic plagiarism detection plays a crucial role by aiming to
identify instances of plagiarized content within a document and determining whether parts of …

The aim of modern authorship attribution approaches is to analyze known authors and to
assign authorships to previously unseen and unlabeled text documents based on various …

Fast and easy access to a wide range of documents in various languages, in conjunction
with the wide availability of translation and editing tools, has led to the need to develop …