Name
Abstract | ||
|---|---|---|
Plagiarism of material from the Internet is a widespread and growing problem.
Several methods used to detect the plagiarism and similarity between the source
document and suspected documents such as fingerprint based on character or
n-gram. In this paper, we discussed a new method to detect the plagiarism based
on graph representation; however, Preprocessing for each document is required
such as breaking down the document into its constituent sentences. Segmentation
of each sentence into separated terms and stop word removal. We build the graph
by grouping each sentence terms in one node, the resulted nodes are connected
to each other based on order of sentence within the document, all nodes in
graph are also connected to top level node "Topic Signature". Topic signature
node is formed by extracting the concepts of each sentence terms and grouping
them in such node. The main advantage of the proposed method is the topic
signature which is main entry for the graph is used as quick guide to the
relevant nodes. which should be considered for the comparison between source
documents and suspected one. We believe the proposed method can achieve a good
performance in terms of effectiveness and efficiency. |
Year | Venue | Keywords |
|---|---|---|
2010 | Clinical Orthopaedics and Related Research | graph representation |
Field | DocType | Volume |
Information retrieval,Plagiarism detection,Segmentation,Computer science,Theoretical computer science,Preprocessor,Source document,Sentence,Stop words,Graph (abstract data type),The Internet | Journal | abs/1004.4 |
ISSN | Citations | PageRank |
Journal of Computing, Volume 2, Issue 4, April 2010 | 2 | 0.38 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ahmed Hamza Osman | 1 | 53 | 4.45 |
| Naomie Salim | 2 | 424 | 48.23 |
| Mohammed Salem Binwahlan | 3 | 67 | 4.70 |