Document Plagiarism Detection Using a New Concept Similarity in Formal Concept Analysis

Muangprathub, Jirapond; Kajornkasirat, Siriwan; Wanichsombat, Apirat

doi:10.1155/2021/6662984

Cited by 15 publications

(7 citation statements)

References 25 publications

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“…A sentence is considered plagiarized when the similarity score between the suspect and the corpus vectors exceeds a certain threshold [33]. This study's threshold is 0.7% or 70%.…”

Section: Decision Makingmentioning

confidence: 99%

An improved extrinsic monolingual plagiarism detection approach of the Bengali text

Ahnaf

Hasan

Sworna

et al. 2023

IJECE

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Plagiarism is an act of literature fraud, which is presenting others’ work or ideas without giving credit to the original work. All published and unpublished written documents are under the cover of this definition. Plagiarism, which increased significantly over the last few years, is a concerning issue for students, academicians, and professionals. Due to this, there are several plagiarism detection tools or software available to detect plagiarism in different languages. Unfortunately, negligible work has been done and no plagiarism detection software available in the Bengali language where Bengali is one of the most spoken languages in the world. In this paper, we have proposed a plagiarism detection tool for the Bengali language that mainly focuses on the educational and newspaper domain. We have collected 82 textbooks from the National Curriculum of Textbooks (NCTB), Bangladesh, scrapped all articles from 12 reputed newspapers and compiled our corpus with more than 10 million sentences. The proposed method on Bengali text corpus shows an accuracy rate of 97.31%

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“…A sentence is considered plagiarized when the similarity score between the suspect and the corpus vectors exceeds a certain threshold [33]. This study's threshold is 0.7% or 70%.…”

Section: Decision Makingmentioning

confidence: 99%

An improved extrinsic monolingual plagiarism detection approach of the Bengali text

Ahnaf

Hasan

Sworna

et al. 2023

IJECE

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“…Muangorathub et al [5] proposed a novel approach of plagiarism detection using formal concept analysis (FCA). The work showed formal context in FCA, starting with two sets containing elements with some attributes that somehow relate the element to its set.…”

Section: B Literature Reviewmentioning

confidence: 99%

“…Several attempts have been made in the past to solve this problem [3], [4], [5], but there is still room for improvements, some of which is discussed in this paper.…”

Section: Introductionmentioning

confidence: 99%

“…Much work has been done on the topic of subjective answers evaluation in one form or another, such as measuring Similarity between different texts, words, and even documents, finding the context behind the text and mapping it with the solution's context, counting the noun-phrase in the documents, matching keywords in the answers, and so on. However, problems such as Tf-Idf loosing semantic context [6], lack of hyper-parameters tuning [7], costly training [8], and need for better datasets [5] still exist.…”

Section: Introductionmentioning

confidence: 99%

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Subjective Answers Evaluation Using Machine Learning and Natural Language Processing

Bashir

Arshad

Javed³

et al. 2021

IEEE Access

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Subjective paper evaluation is a tricky and tiresome task to do by manual labor. Insufficient understanding and acceptance of data are crucial challenges while analyzing subjective papers using Artificial Intelligence (AI). Several attempts have been made to score students' answers using computer science. However, most of the work uses traditional counts or specific words to achieve this task. Furthermore, there is a lack of curated data sets as well. This paper proposes a novel approach that utilizes various machine learning, natural language processing techniques, and tools such as Wordnet, Word2vec, word mover's distance (WMD), cosine similarity, multinomial naive bayes (MNB), and term frequencyinverse document frequency (TF-IDF) to evaluate descriptive answers automatically. Solution statements and keywords are used to evaluate answers, and a machine learning model is trained to predict the grades of answers. Results show that WMD performs better than cosine similarity overall. With enough training, the machine learning model could be used as a standalone as well. Experimentation produces an accuracy of 88% without the MNB model. The error rate is further reduced by 1.3% using MNB.

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“…According to Ehsan et al [14], plagiarism detection methods are divided into two main categories, which are intrinsic plagiarism detection and external plagiarism detection methods. Intrinsic methods are implemented to detect the parts of the text that are inconsistent, while external methods can match suspicious passages in a text to the source(s), detecting exact verbatim copying and paraphrased text [23].…”

Section: Introductionmentioning

confidence: 99%

A Paraphrase Identification Approach in Paragraph Length Texts

Saqaabi

Akrida

Cristea

et al. 2022

2022 IEEE International Conference on Data Mining Workshops (ICDMW)

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How to measure the semantic similarity of natural language is a fundamental issue in many tasks, such as paraphrase identification (PI) and plagiarism detection (PD) which are intended to solve major issues in education. There are many approaches that have been suggested, such as machine learning (ML) and deep learning (DL) methods. Unlike in prior research, where detecting paraphrases in short and sentence-level texts has been done, we focus on the not yet explored area of paraphrase detection in paragraphs. We consider that the meaning of a piece of text can be broken into more than one sentence, this is over and above the sentences as extracted from two benchmark datasets (Webis-CPC-11 and MSRP). TF-IDF, Bleu metric, N-gram overlap, and Word2vec are used as features, then SVM is invoked as a classifier. The contribution of this paper clearly indicates that, on a commonly used evaluation set, text at the length of a paragraph is more appropriate to consider than short or long text for ML and DL approaches. Additionally, our method outperforms the existing work done on the Webis-CPC-11 dataset.

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Document Plagiarism Detection Using a New Concept Similarity in Formal Concept Analysis

Cited by 15 publications

References 25 publications

An improved extrinsic monolingual plagiarism detection approach of the Bengali text

An improved extrinsic monolingual plagiarism detection approach of the Bengali text

Subjective Answers Evaluation Using Machine Learning and Natural Language Processing

A Paraphrase Identification Approach in Paragraph Length Texts

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