Name
Abstract | ||
|---|---|---|
Plagiarism has become one area of interest for re-searchers due to its importance, and its fast growing rates. Effective clustering methods and faster search tools for matching and discovering the similarities between documents were the main two areas for the researchers. Many tools and techniques have been developed for plagiarism detection. In this paper we use singular value decomposition for its effective clustering of the documents in-order to reduce search time by creating a new matrix with fewer dimensions used for clustering the original (source) documents, and we use Neural Networks for local matching and comparison between a suspicious document and a source document, Kohonen maps (Self-organizing maps (SOM)) used to visualized and comparison of the result, in which represent the result as picture that easier to be analyzed. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/CICSyN.2011.25 | CICSyN |
Keywords | Field | DocType |
pattern clustering,self-organising feature maps,singular value decomposition,text analysis,Kohonen maps,document clustering methods,document similarities,neural networks,plagiarism detection,search tools,self-organizing maps,singular value decomposition,Kohonen Maps,Plagiarism Detection,Singular Value Decomposition | Data mining,Singular value decomposition,Data visualization,Plagiarism detection,Pattern recognition,Computer science,Matrix decomposition,Self-organizing map,Artificial intelligence,Artificial neural network,Cluster analysis,Sparse matrix | Conference |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Asim M. El Tahir Ali | 1 | 0 | 0.34 |
| Hussam M. Dahwa Abdulla | 2 | 0 | 1.01 |
| Václav Snasel | 3 | 1261 | 210.53 |
| Ivo Vondrak | 4 | 2 | 1.09 |