Sources Of Plagiarism Research Articles

Automatic Detection of Plagiarism in Writing

This paper reports on preliminary steps to create an external plagiarism detection tool. I used the PAN-PC-11 data sets and extracted tf-idf scores of text documents and cosine similarity measures between source and suspicious documents to find text overlap. The model was able to successfully create vectors and measure the similarity metrics. However, the algorithm was not extended further to automatically retrieve related documents to follow on the pipeline (converting texts to n-grams for detailed analysis and revealing the best match as a source of plagiarism and evaluating the accuracy of the model). The model produced a matrix of cosine similarity for all the documents, which I used to manually retrieve documents and check for overlap using online tools. While extending the algorithm based on the suggested pipeline would allow for a more accurate evaluation of the model, manual comparison of sample documents provided some validity of the model developed for the present study.

Perceptions and Experiences of Academic Integrity and Group Work in Post-Graduate Management Courses: Strategies and Risks

Student perceptions of group assignments indicate that there are lower levels of plagiarism or contract cheating in these assessments given the collective nature of the work, while individual assignments, particularly reports, are perceived as easier to cheat in. This paper examines the perceptions and the experiences of post-graduate management students and teaching staff in the level, type and source of plagiarism as it relates to group versus individual assignments. It compares the views of the academic literature on plagiarism with the student’s own perceptions and with the tendency to cheat in different forms of group and individual assessment. It further presents strategies for the mitigation of academic plagiarism and evaluates the risks arising from over-dependence on group assessments in an attempt to minimise plagiarism. Practical implications as well as theoretical concepts are addressed that may help develop effective strategies to address academic plagiarism.

Online art class: a study on the cause and effect of plagiarism

This study discusses the problem of plagiarism in art learning in online classes. The art class was conducted using the Learning Management System (LMS) and attended by 31 Pendidikan Anak Usia Dini (PAUD) students, and arts department. This research method uses a survey derived from two types of data. The first data was obtained from a questionnaire distributed to 211 art students. Factors that determine copy-paste occur because of the tendency to postpone tasks, so they work at the end of time. The following data comes from the discussion assignment report done by the student. Tasks are scanned online using the application. The results of the analysis of plagiarism showed an average of 49.09%, with a word similarity level of 80.77%. Based on online scan reports, the source of plagiarism comes from the university repository. Students use Open Educational Resource (OER) in the form of dictates as material for doing art lecture assignments. In conclusion, students mistakenly understood the use of OER and digital literacy. Digital-based arts learning does not have a significant impact and requires the provision of academic writing. Keywords: Art Learning, LMS, OER, Digital Literacy, Plagiarism

Source Retrieval Model Focused on Aggregation for plagiarism detection

Source retrieval for plagiarism detection retrieves documents that may be the sources of plagiarism for a suspicious document while minimizing the retrieval costs. Compared with traditional information retrieval, queries from the same suspicious document retain their contextual relations and are no longer isolated from each other. The correlation of queries leads to the aggregation of search results; the documents retrieved by different queries may be relevant or the same. However, previous studies have failed to devote sufficient attention to the aggregation of search results in source retrieval. In this paper, the task of source retrieval is formalized into a framework of learning to rank, and a Ranking Logistical Regression Model is utilized to implement the framework. Furthermore, addressing the aggregation of search results, we propose the Source Retrieval Model Focused on Aggregation for plagiarism detection. We evaluate various aspects of the proposed model on the PAN 2013 and the PAN 2014 Plagiarism Source Retrieval Corpus. With respect to established baselines, the experimental results indicate that the Source Retrieval Model Focused on Aggregation yields statistically significantly improved performance of source retrieval with equal or lower cost effectiveness.

BHA2

In the last decade, the plagiarism cases were increased and become a topical problem in the modern scientific world, caused by the quantity of textual information available online/offline. The authors' work deals on the development of a new plagiarism detector system called BHA2 which has as input the suspicious text (to be analysed) and the original texts (learning basis). It can detect the different forms of plagiarism based on: Google API to detect the cases of plagiarism with translation; text summarization to detect the plagiarism of idea; conceptual transformation to detect the plagiarism with synonymy; bag of phrases to detect the paraphraser plagiarism; the social worker bees algorithm that was inspired from the lifestyle of social worker bees (forager, guardian, and cleaner) to select the documents source of plagiarism; the output of the authors' system are the plagiarised passages (the copied parts from the original texts) and the plagiarism percentage for each suspicious text. Their experiments were performed on the Pan 09 dataset and using the validation measures (recall, precision, accuracy, error, f-measure, and entropy, FPR, FNR, W-accuracy, ROC and TCR) in order to show the benefit derived from using such idea compared to the result of classical systems existed in literature. A comparative study in term of services was realised between their system and others commercial systems such as (check, Turnitin, and machine learning system) with their system. Finally, a visualization step was achieved for the purpose to see the outcome in graphical form (3d cub and cobweb) with more realism using the functionalities of zooming and rotation.

An IR-Based Approach Utilizing Query Expansion for Plagiarism Detection in MEDLINE.

The identification of duplicated and plagiarized passages of text has become an increasingly active area of research. In this paper, we investigate methods for plagiarism detection that aim to identify potential sources of plagiarism from MEDLINE, particularly when the original text has been modified through the replacement of words or phrases. A scalable approach based on Information Retrieval is used to perform candidate document selection-the identification of a subset of potential source documents given a suspicious text-from MEDLINE. Query expansion is performed using the ULMS Metathesaurus to deal with situations in which original documents are obfuscated. Various approaches to Word Sense Disambiguation are investigated to deal with cases where there are multiple Concept Unique Identifiers (CUIs) for a given term. Results using the proposed IR-based approach outperform a state-of-the-art baseline based on Kullback-Leibler Distance.

Plagiarism Detector: Assessing Quality of Undergraduate Teacher Education Researches

The study assessed the quality of undergraduate researchers of the College of Teacher Education of one of the leading universities in Cebu from School Year 2008 to 2012. Also, the study determined the percentage ratings of plagiarism and identified sources of plagiarism in the research specimens. The study utilized documentary analysis to elicit information on the extent of piracy. The researchers used stratified sampling to select 41 research samples. The researchers used frequency counts, percentage, and average growth rate to gather information from the research specimens. The findings suggested that plagiarism is increased by 28% every year. Furthermore, the results showed that there were a significant number of validated cases of plagiarism on the research specimens. Also, the findings showed that undergraduate students get more information from the non–authoritative source than from reliable sources of information. The study recommended the acquisition of plagiarism detector software that is necessary for assessing the quality of undergraduate researchers. Keywords-Education, Undergraduate Research, plagiarism, sources of piracy, plagiarism detector software, descriptive design, Philippines

Efficacy of Plagiarism Detection Software for Quality Assurance of a Research Journal

Plagiarism in research undermines credibility of journal publications. Plagiarism detection addresses this problem. The study validated the efficacy of the plagiarism detector software for quality assurance of a journal publication. Using descriptive method, the study examined 66 plagiarism detector reports and compared the extent of originality and plagiarism of the research article before and after adoption of the plagiarism detector accumulator technology. Results revealthat the journal had a high level of originality (91.31%) and low level of plagiarism (8.34%). Only 23.72 percentof the 550 detected cases were validated as true plagiarism, giving the software an efficacy rate of 24 percent. The sources of plagiarism included the web links, wikipedia, news, social networking sites, and blogs, among others. The use of these sources indicated the citation of grey literature and non-authoritative sources. Failure to properly document sources was the main cause of plagiarism. The software, however, cannot penetrate the secured databases of subscription journals-thus; plagiarism from these sources evades detection. Plagiarism detection software is effective in intercepting plagiarized sources which elude the scrutiny of the editorial board prior to final publication. The editorial board’s strong quality assurance mechanism and the intervention scheme reduced the incidents of plagiarism in 2009. Keywords - plagiarism, plagiarism detection software, journal publication, originality

Using structural information and citation evidence to detect significant plagiarism cases in scientific publications

AbstractIn plagiarism detection (PD) systems, two important problems should be considered: the problem of retrieving candidate documents that are globally similar to a document q under investigation, and the problem of side‐by‐side comparison of q and its candidates to pinpoint plagiarized fragments in detail. In this article, the authors investigate the usage of structural information of scientific publications in both problems, and the consideration of citation evidence in the second problem. Three statistical measures namely Inverse Generic Class Frequency, Spread, and Depth are introduced to assign a degree of importance (i.e., weight) to structural components in scientific articles. A term‐weighting scheme is adjusted to incorporate component‐weight factors, which is used to improve the retrieval of potential sources of plagiarism. A plagiarism screening process is applied based on a measure of resemblance, in which component‐weight factors are exploited to ignore less or nonsignificant plagiarism cases. Using the notion of citation evidence, parts with proper citation evidence are excluded, and remaining cases are suspected and used to calculate the similarity index. The authors compare their approach to two flat‐based baselines, TF‐IDF weighting with a Cosine coefficient, and shingling with a Jaccard coefficient. In both baselines, they use different comparison units with overlapping measures for plagiarism screening. They conducted extensive experiments using a dataset of 15,412 documents divided into 8,657 source publications and 6,755 suspicious queries, which included 18,147 plagiarism cases inserted automatically. Component‐weight factors are assessed using precision, recall, and F‐measure averaged over a 10‐fold cross‐validation and compared using the ANOVA statistical test. Results from structural‐based candidate retrieval and plagiarism detection are evaluated statistically against the flat baselines using paired‐t tests on 10‐fold cross‐validation runs, which demonstrate the efficacy achieved by the proposed framework. An empirical study on the system's response shows that structural information, unlike existing plagiarism detectors, helps to flag significant plagiarism cases, improve the similarity index, and provide human‐like plagiarism screening results.

Alta frecuencia de plagio en tesis de medicina de una universidad pública peruana

An observational study was conducted to describe the presence of plagiarism in medical thesis in 2008 performed at a public university in Peru. Search for plagiarism in 33 thesis introductions using a Google search algorithm, characterizes of the study type and we search in electronic form if the thesis mentor have published articles in scientific journals. We found evidence of plagiarism in 27/33 introductions, 37.3% (171/479) of all the paragraphs analyzed had some degree of plagiarism, literal plagiarism was the most frequent (20/27) and journals were the most common sources of plagiarism (19/27). The characteristics of the studies were observational (32/33), cross-sectional (30/33), descriptive (25/33) and retrospective (19/33). None of the authors had published in a scientific journal, and only nine of his tutors of them had at least one publication. No association was found between the characteristics of the thesis and the presence of plagiarism. In conclusion, we found a high frequency of plagiarism in theses analyzed. Is responsibility of medical schools take the necessary actions to detect and avoid plagiarism among their students.

Alta frecuencia de plagio en tesis de medicina de una universidad pública Peruana

An observational study was conducted to describe the presence of plagiarism in medical thesis in 2008 performed at a public university in Peru. Search for plagiarism in 33 thesis introductions using a Google search algorithm, characterizes of the study type and we search in electronic form if the thesis mentor have published articles in scientific journals. We found evidence of plagiarism in 27/33 introductions, 37.3% (171/479) of all the paragraphs analyzed had some degree of plagiarism, literal plagiarism was the most frequent (20/27) and journals were the most common sources of plagiarism (19/27). The characteristics of the studies were observational (32/33), cross-sectional (30/33), descriptive (25/33) and retrospective (19/33). None of the authors had published in a scientific journal, and only nine of his tutors of them had at least one publication. No association was found between the characteristics of the thesis and the presence of plagiarism. In conclusion, we found a high frequency of plagiarism in theses analyzed. Is responsibility of medical schools take the necessary actions to detect and avoid plagiarism among their students.