Application of Java Relationship Graphs (JRG) to plagiarism detection in Java Projects: A Neo4j Graph Database Approach

Author(s):  
Ritu Arora ◽  
Arun Motilal Maurya ◽  
Yashvardhan Sharma
2020 ◽  
Vol 4 (5) ◽  
pp. 988-997
Author(s):  
Sylvia Putri Gunawan ◽  
Lucia Dwi Krisnawati ◽  
Antonius Rachmat Chrismanto

Two different paradigms in the field of plagiarism detection resulting in External Plagiarism Detection (EPD) and Intrinsic Plagiarism Detection (IPD) systems. The most common applied system is EPD, which requires its algorithm to make a heuristic comparison between a suspicious document with documents in a corpus. In contrast, given a suspicious document only, an algorithm of IPD should be able to find the plagiarism section by looking for text segments having different writing styles. Previous researches for Indonesian texts fell only in the field of the EPD development system. Therefore, this research focuses on and contributes to experimenting and analyzing the stylometric features and segmentation strategies to build an IPD system for Indonesian texts. The experimentation results show that the paragraph segment performs better by scoring 0.92 for Macro Averaged-Accuracy and 0.54 for Macro Averaged-F1. The stylometric features achieving the highest scores of F-1 and Accuracy are the frequency of punctuation, the average paragraph length, and the type-token ratio.  


Computers ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 47
Author(s):  
Fariha Iffath ◽  
A. S. M. Kayes ◽  
Md. Tahsin Rahman ◽  
Jannatul Ferdows ◽  
Mohammad Shamsul Arefin ◽  
...  

A programming contest generally involves the host presenting a set of logical and mathematical problems to the contestants. The contestants are required to write computer programs that are capable of solving these problems. An online judge system is used to automate the judging procedure of the programs that are submitted by the users. Online judges are systems designed for the reliable evaluation of the source codes submitted by the users. Traditional online judging platforms are not ideally suitable for programming labs, as they do not support partial scoring and efficient detection of plagiarized codes. When considering this fact, in this paper, we present an online judging framework that is capable of automatic scoring of codes by detecting plagiarized contents and the level of accuracy of codes efficiently. Our system performs the detection of plagiarism by detecting fingerprints of programs and using the fingerprints to compare them instead of using the whole file. We used winnowing to select fingerprints among k-gram hash values of a source code, which was generated by the Rabin–Karp Algorithm. The proposed system is compared with the existing online judging platforms to show the superiority in terms of time efficiency, correctness, and feature availability. In addition, we evaluated our system by using large data sets and comparing the run time with MOSS, which is the widely used plagiarism detection technique.


2021 ◽  
Vol 22 (S2) ◽  
Author(s):  
Daniele D’Agostino ◽  
Pietro Liò ◽  
Marco Aldinucci ◽  
Ivan Merelli

Abstract Background High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of DNA interactions and 3D chromosome folding at the genome-wide scale. Usually, these data are represented as matrices describing the binary contacts among the different chromosome regions. On the other hand, a graph-based representation can be advantageous to describe the complex topology achieved by the DNA in the nucleus of eukaryotic cells. Methods Here we discuss the use of a graph database for storing and analysing data achieved by performing Hi-C experiments. The main issue is the size of the produced data and, working with a graph-based representation, the consequent necessity of adequately managing a large number of edges (contacts) connecting nodes (genes), which represents the sources of information. For this, currently available graph visualisation tools and libraries fall short with Hi-C data. The use of graph databases, instead, supports both the analysis and the visualisation of the spatial pattern present in Hi-C data, in particular for comparing different experiments or for re-mapping omics data in a space-aware context efficiently. In particular, the possibility of describing graphs through statistical indicators and, even more, the capability of correlating them through statistical distributions allows highlighting similarities and differences among different Hi-C experiments, in different cell conditions or different cell types. Results These concepts have been implemented in NeoHiC, an open-source and user-friendly web application for the progressive visualisation and analysis of Hi-C networks based on the use of the Neo4j graph database (version 3.5). Conclusion With the accumulation of more experiments, the tool will provide invaluable support to compare neighbours of genes across experiments and conditions, helping in highlighting changes in functional domains and identifying new co-organised genomic compartments.


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