Document Plagiarism Detection Using a New Concept Similarity in Formal Concept Analysis
This paper proposes an algorithm for document plagiarism detection using the provided incremental knowledge construction with formal concept analysis (FCA). The incremental knowledge construction is presented to support document matching between the source document in storage and the suspect documen...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2021/6662984 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849306723866640384 |
|---|---|
| author | Jirapond Muangprathub Siriwan Kajornkasirat Apirat Wanichsombat |
| author_facet | Jirapond Muangprathub Siriwan Kajornkasirat Apirat Wanichsombat |
| author_sort | Jirapond Muangprathub |
| collection | DOAJ |
| description | This paper proposes an algorithm for document plagiarism detection using the provided incremental knowledge construction with formal concept analysis (FCA). The incremental knowledge construction is presented to support document matching between the source document in storage and the suspect document. Thus, a new concept similarity measure is also proposed for retrieving formal concepts in the knowledge construction. The presented concept similarity employs appearance frequencies in the obtained knowledge construction. Our approach can be applied to retrieve relevant information because the obtained structure uses FCA in concept form that is definable by a conjunction of properties. This measure is mathematically proven to be a formal similarity metric. The performance of the proposed similarity measure is demonstrated in document plagiarism detection. Moreover, this paper provides an algorithm to build the information structure for document plagiarism detection. Thai text test collections are used for performance evaluation of the implemented web application. |
| format | Article |
| id | doaj-art-2d9792fd8e714962af2585ee278c18f4 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-2d9792fd8e714962af2585ee278c18f42025-08-20T03:55:00ZengWileyJournal of Applied Mathematics1110-757X1687-00422021-01-01202110.1155/2021/66629846662984Document Plagiarism Detection Using a New Concept Similarity in Formal Concept AnalysisJirapond Muangprathub0Siriwan Kajornkasirat1Apirat Wanichsombat2Faculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Surat Thani 84000, ThailandFaculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Surat Thani 84000, ThailandFaculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Surat Thani 84000, ThailandThis paper proposes an algorithm for document plagiarism detection using the provided incremental knowledge construction with formal concept analysis (FCA). The incremental knowledge construction is presented to support document matching between the source document in storage and the suspect document. Thus, a new concept similarity measure is also proposed for retrieving formal concepts in the knowledge construction. The presented concept similarity employs appearance frequencies in the obtained knowledge construction. Our approach can be applied to retrieve relevant information because the obtained structure uses FCA in concept form that is definable by a conjunction of properties. This measure is mathematically proven to be a formal similarity metric. The performance of the proposed similarity measure is demonstrated in document plagiarism detection. Moreover, this paper provides an algorithm to build the information structure for document plagiarism detection. Thai text test collections are used for performance evaluation of the implemented web application.http://dx.doi.org/10.1155/2021/6662984 |
| spellingShingle | Jirapond Muangprathub Siriwan Kajornkasirat Apirat Wanichsombat Document Plagiarism Detection Using a New Concept Similarity in Formal Concept Analysis Journal of Applied Mathematics |
| title | Document Plagiarism Detection Using a New Concept Similarity in Formal Concept Analysis |
| title_full | Document Plagiarism Detection Using a New Concept Similarity in Formal Concept Analysis |
| title_fullStr | Document Plagiarism Detection Using a New Concept Similarity in Formal Concept Analysis |
| title_full_unstemmed | Document Plagiarism Detection Using a New Concept Similarity in Formal Concept Analysis |
| title_short | Document Plagiarism Detection Using a New Concept Similarity in Formal Concept Analysis |
| title_sort | document plagiarism detection using a new concept similarity in formal concept analysis |
| url | http://dx.doi.org/10.1155/2021/6662984 |
| work_keys_str_mv | AT jirapondmuangprathub documentplagiarismdetectionusinganewconceptsimilarityinformalconceptanalysis AT siriwankajornkasirat documentplagiarismdetectionusinganewconceptsimilarityinformalconceptanalysis AT apiratwanichsombat documentplagiarismdetectionusinganewconceptsimilarityinformalconceptanalysis |