Plagiarism detection

About: Plagiarism detection is a research topic. Over the lifetime, 1790 publications have been published within this topic receiving 24740 citations.

Plagiarism detection scheme based on Semantic Role Labeling

Abstract: Nowadays, many documents are available on the internet and are easy to access Due to this wide availability, users can easily create a new document by copying and pasting Plagiarism occurs when the content is copied without permission or citation This paper introduces a plagiarism detection technique based on the Semantic Role Labeling (SRL) The technique analyses and compares text based on the semantic allocation for each term inside the sentence SRL is superior in generating arguments for each sentence semantically In addition, experimental results on PAN-PC-09 data sets showed that our method outperforms the modern methods for plagiarism detection in terms of Recall, Precision and F-measure

Improved Plagiarism Detection Algorithm Based on Abstract Syntax Tree

Abstract: Statements with conditionals are widely used in C, C++ and java, such as if and while statements and they are easy to plagiarize by adjusting the logical structure of the corresponding statements. However, the existing relative algorithms and tools cannot effectively detect code plagiarism of these statements. This paper puts forward an improved code plagiarism detection algorithm based on abstract syntax tree. The algorithm calculates the hash value for each node of the abstract syntax tree, and compares the hash values node by node. Based on this, it analyzes the if-statement plagiarism, as if-statements are representative in the statements with conditionals, and puts forward the corresponding detection schemes in order to detect plagiarism effectively. After that, with the results of many experiments, the algorithm is proved effective on detecting if-statement plagiarisms.

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

Abstract: This paper proposes an algorithm for document plagiarism detection using the provided incremental knowledge construction with formal concept analysis (FCA). The incremental knowledge construction is presented to support document matching between the source document in storage and the suspect document. Thus, a new concept similarity measure is also proposed for retrieving formal concepts in the knowledge construction. The presented concept similarity employs appearance frequencies in the obtained knowledge construction. Our approach can be applied to retrieve relevant information because the obtained structure uses FCA in concept form that is definable by a conjunction of properties. This measure is mathematically proven to be a formal similarity metric. The performance of the proposed similarity measure is demonstrated in document plagiarism detection. Moreover, this paper provides an algorithm to build the information structure for document plagiarism detection. Thai text test collections are used for performance evaluation of the implemented web application.

Detecting plagiarized mobile apps using API birthmarks

Abstract: This paper addresses the problem of detecting plagiarized mobile apps. Plagiarism is the practice of building mobile apps by reusing code from other apps without the consent of the corresponding app developers. Recent studies on third-party app markets have suggested that plagiarized apps are an important vehicle for malware delivery on mobile phones. Malware authors repackage official versions of apps with malicious functionality, and distribute them for free via these third-party app markets. An effective technique to detect app plagiarism can therefore help identify malicious apps. Code plagiarism has long been a problem and a number of code similarity detectors have been developed over the years to detect plagiarism. In this paper we show that obfuscation techniques can be used to easily defeat similarity detectors that rely solely on statically scanning the code of an app. We propose a dynamic technique to detect plagiarized apps that works by observing the interaction of an app with the underlying mobile platform via its API invocations. We propose API birthmarks to characterize unique app behaviors, and develop a robust plagiarism detection tool using API birthmarks.

That site looks 88.46% familiar: quantifying similarity of Web page design

Abstract: Web page design guidelines produce a pressure towards uniformity; excessive uniformity lays a Web page designer open to accusations of plagiarism. In the past, assessment of similarity between visual products such as Web pages has involved an uncomfortably high degree of subjectivity. This paper describes a method for measuring perceived similarity of visual products which avoids previous problems with subjectivity, and which makes it possible to pool results from respondents without the need for intermediate coding. This method is based on co-occurrence matrices derived from card sorts. It can also be applied to other areas of software development, such as systems analysis and market research.