The article entitled “PDLK: Plagiarism detection using linguistic knowledge” by the joint collaboration of the scientists of the Institute was published in an international journal “Expert Systems with Applications”.

The authors of the article are Asad Abdi, Norisma Idris, academician Rasim M. Alguliyev and Doctor of Technical Sciences Ramiz M. Aliguliyev.

This paper presents a method to detect external plagiarism using the integration of semantic relations between words and their syntactic composition. The problem with the available methods is that they fail to capture the meaning in comparison between a source document sentence and a suspicious document sentence, when two sentences have same surface text (the words are the same) or they are a paraphrase of each other. Therefore, it causes inaccurate or unnecessary matching results. However, this method can improve the performance of plagiarism detection because it is able to avoid selecting the source text sentence whose similarity with suspicious text sentence is high, but its meaning is different. It is executed by computing the semantic and syntactic similarity of the sentence-to-sentence. The experimental results also displayed that the proposed method demonstrates better performance as compared to other existing techniques on PAN-PC-10 and PAN-PC-11 datasets.

Impact Factor: 2.240

5-Year ImpactFactor: 2.571

Source Normalized Impact per Paper (SNIP): 2.534

SCImago Journal Rank (SJR): 1.996.

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