scholarly journals Implementation of Winnowing Algorithm Based K-Gram to Identify Plagiarism on File Text-Based Document

2018 ◽  
Vol 164 ◽  
pp. 01048
Author(s):  
Yanuar Nurdiansyah ◽  
Fiqih Nur Muharrom ◽  
Firdaus
Keyword(s):  
Similarity Search ◽  
Search Algorithm ◽  
Detection System ◽  
Jaccard Coefficient ◽  
Plagiarism Detection ◽  
Document Similarity ◽  
Calculation Process ◽  
Waterfall Model ◽  
Two Stages ◽  
Model Approach

Plagiarism occurs when the students have tasks and pursued by the deadline. Plagiarism is considered as the fastest way to accomplish the tasks. This reason makes the author tried to build a plagiarism detection system with Winnowing algorithm as document similarity search algorithm. The documents that being tested are Indonesian journals with extension .doc, .docx, and/or .txt. Similarity calculation process through two stages, the first is the process of making a document fingerprint using Winnowing algorithm and the second is using Jaccard coefficient similarity. In order to develop this system, the author used iterative waterfall model approach. The main objective of this project is to determine the level of plagiarism. It is expected to prevent plagiarism either intentionally or unintentionally before our journal published by displaying the percentage of similarity in the journals that we make.

Analysis of Stylometric Features and Segmentation Strategies in Intrinsic Plagiarism Detection System

2020 ◽  
Vol 4 (5) ◽  
pp. 988-997
Author(s):  
Sylvia Putri Gunawan ◽  
Lucia Dwi Krisnawati ◽  
Antonius Rachmat Chrismanto
Keyword(s):  
Detection System ◽  
Plagiarism Detection ◽  
Development System ◽  
Intrinsic Plagiarism Detection

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.  

scholarly journals A support vector machine with the tabu search algorithm for freeway incident detection

2014 ◽  
Vol 24 (2) ◽  
pp. 397-404 ◽  
Author(s):  
Baozhen Yao ◽  
Ping Hu ◽  
Mingheng Zhang ◽  
Maoqing Jin
Keyword(s):  
Support Vector Machine ◽  
Tabu Search ◽  
Traffic Management ◽  
Search Algorithm ◽  
Detection System ◽  
Support Vector ◽  
Incident Detection ◽  
Tabu Search Algorithm ◽  
Proposed Model ◽  
Parameter Values

Abstract Automated Incident Detection (AID) is an important part of Advanced Traffic Management and Information Systems (ATMISs). An automated incident detection system can effectively provide information on an incident, which can help initiate the required measure to reduce the influence of the incident. To accurately detect incidents in expressways, a Support Vector Machine (SVM) is used in this paper. Since the selection of optimal parameters for the SVM can improve prediction accuracy, the tabu search algorithm is employed to optimize the SVM parameters. The proposed model is evaluated with data for two freeways in China. The results show that the tabu search algorithm can effectively provide better parameter values for the SVM, and SVM models outperform Artificial Neural Networks (ANNs) in freeway incident detection.

Distributed similarity search algorithm in distributed heterogeneous multimedia databases

2000 ◽  
Vol 75 (1-2) ◽  
pp. 35-42 ◽  
Author(s):  
Ju-Hong Lee ◽  
Deok-Hwan Kim ◽  
Seok-Lyong Lee ◽  
Chin-Wan Chung ◽  
Guang-Ho Cha
Keyword(s):  
Similarity Search ◽  
Search Algorithm ◽  
Multimedia Databases

scholarly journals An Effective System of Intrusion Detection on Deep Neural Network by Hybrid Optimization in Cyber Security

2019 ◽  
Vol 9 (1) ◽  
pp. 1320-1327
Keyword(s):  
Intrusion Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Search Algorithm ◽  
Detection System ◽  
Optimization Techniques ◽  
Hybrid Optimization ◽  
Experimental Result ◽  
Gray Wolf ◽  
High Detection

In present trends organizations are very much interested to protect data and prevent malware attack by using well flourished and excellent tools. Many algorithms are used for the intrusion detection system (IDS) and it has pros and cons. Here we proposed a novel method of intrusion detection using hybrid optimization techniques such as Gravity search algorithm with gray wolf optimization (GSGW). In this method the gray wolf technique has a leader for the continuous monitoring of the attacker and has a low false alarm rate and a high detection rate. The performance evaluation is done by the feature selection in NSL-KDD dataset. In the proposed method the experimental result reveals less false alarm rate, better accuracy and high Detection when compared to previous analysis.

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