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Research on Literature Similarity Detection Based on Semantic Role Labeling
Received date: 2014-04-30
Revised date: 2014-06-03
Online published: 2014-06-20
In recent years, several academic misconducts have caught the attention of both the academic community and departments concerned which makes similarity detection a hot research point. To cope with semantic plagiarism, researchers begin to study the semantic information. This paper proposes a literature semantic similarity detection method based on semantic role labeling. First a paper is labeled using a SRL tool. Sentence granularity is used. Hypernyms were extracted using a semantic dictionary. Every paper is represented by a sentence-term-semantic role-hypernym 4-partite graph. Sentence comparison refers to the 4-partite graph. Jaccard coefficient is computed to represent the similarity between two papers. Due to the confinement of SRL tools, the result of semantic similarity detection is not agreeable. Even so it is still 13% higher than other methods.
Wang Xiaodi , Zhu Na , Bai Rujiang , Wang Xiaoyue . Research on Literature Similarity Detection Based on Semantic Role Labeling[J]. Library and Information Service, 2014 , 58(12) : 130 -135 . DOI: 10.13266/j.issn.0252-3116.2014.12.020
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