Presenting a method to reduce the sensitivity of incremental clustering algorithms of XML documents based on collective intelligence algorithms
Until now, various methods have been presented for storing and retrieving information of semi-structured documents, most of them are placed in two groups with batch and incremental approach. In the batch or cluster approach, it is assumed that all the documents can be accessed and clustered, and the...
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University of Qom
2024-03-01
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| Series: | مدیریت مهندسی و رایانش نرم |
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| Online Access: | https://jemsc.qom.ac.ir/article_2797_4fd0bcb4a4ac144ed336f085e721857b.pdf |
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| author | Mohammad Nazari Farokhi Ebrahim Nazari Farokhi Ali Norouzbakhsh |
| author_facet | Mohammad Nazari Farokhi Ebrahim Nazari Farokhi Ali Norouzbakhsh |
| author_sort | Mohammad Nazari Farokhi |
| collection | DOAJ |
| description | Until now, various methods have been presented for storing and retrieving information of semi-structured documents, most of them are placed in two groups with batch and incremental approach. In the batch or cluster approach, it is assumed that all the documents can be accessed and clustered, and the documents can be processed several times, which increases the execution time of such algorithms. In the incremental approach, all the documents do not exist in one place, but over time, they are provided to the classification method, and from this point of view, the execution time of such algorithms is less compared to the batch method, and as a result, their execution speed is faster. In this research, our proposed method was compared with XCLS and XCLS+ methods in three evaluation criteria: Entropy, Purity and Fscore. The results showed that the proposed method is preferable to the XCLS and XCLS+ methods in terms of Entropy, Purity and Fscore, and it is slightly less efficient than the XCLS+ method only in the Fscore criterion. |
| format | Article |
| id | doaj-art-c66f379f86364b0d868541051dfded3e |
| institution | Kabale University |
| issn | 2538-6239 2538-2675 |
| language | fas |
| publishDate | 2024-03-01 |
| publisher | University of Qom |
| record_format | Article |
| series | مدیریت مهندسی و رایانش نرم |
| spelling | doaj-art-c66f379f86364b0d868541051dfded3e2025-01-30T20:19:06ZfasUniversity of Qomمدیریت مهندسی و رایانش نرم2538-62392538-26752024-03-019217718710.22091/jemsc.2024.9990.11762797Presenting a method to reduce the sensitivity of incremental clustering algorithms of XML documents based on collective intelligence algorithmsMohammad Nazari Farokhi0Ebrahim Nazari Farokhi1Ali Norouzbakhsh2Department of Management, Faculty of Management, University of Science and Research, Tehran, IranDepartment of Management, Faculty of Management, University of Science and Research, Tehran, IranDepartment of Management, Faculty of Management, University of Science and Research, Tehran, IranUntil now, various methods have been presented for storing and retrieving information of semi-structured documents, most of them are placed in two groups with batch and incremental approach. In the batch or cluster approach, it is assumed that all the documents can be accessed and clustered, and the documents can be processed several times, which increases the execution time of such algorithms. In the incremental approach, all the documents do not exist in one place, but over time, they are provided to the classification method, and from this point of view, the execution time of such algorithms is less compared to the batch method, and as a result, their execution speed is faster. In this research, our proposed method was compared with XCLS and XCLS+ methods in three evaluation criteria: Entropy, Purity and Fscore. The results showed that the proposed method is preferable to the XCLS and XCLS+ methods in terms of Entropy, Purity and Fscore, and it is slightly less efficient than the XCLS+ method only in the Fscore criterion.https://jemsc.qom.ac.ir/article_2797_4fd0bcb4a4ac144ed336f085e721857b.pdfparticle optimization algorithmsemi-structured documentsincremental clusteringcollective intelligence |
| spellingShingle | Mohammad Nazari Farokhi Ebrahim Nazari Farokhi Ali Norouzbakhsh Presenting a method to reduce the sensitivity of incremental clustering algorithms of XML documents based on collective intelligence algorithms مدیریت مهندسی و رایانش نرم particle optimization algorithm semi-structured documents incremental clustering collective intelligence |
| title | Presenting a method to reduce the sensitivity of incremental clustering algorithms of XML documents based on collective intelligence algorithms |
| title_full | Presenting a method to reduce the sensitivity of incremental clustering algorithms of XML documents based on collective intelligence algorithms |
| title_fullStr | Presenting a method to reduce the sensitivity of incremental clustering algorithms of XML documents based on collective intelligence algorithms |
| title_full_unstemmed | Presenting a method to reduce the sensitivity of incremental clustering algorithms of XML documents based on collective intelligence algorithms |
| title_short | Presenting a method to reduce the sensitivity of incremental clustering algorithms of XML documents based on collective intelligence algorithms |
| title_sort | presenting a method to reduce the sensitivity of incremental clustering algorithms of xml documents based on collective intelligence algorithms |
| topic | particle optimization algorithm semi-structured documents incremental clustering collective intelligence |
| url | https://jemsc.qom.ac.ir/article_2797_4fd0bcb4a4ac144ed336f085e721857b.pdf |
| work_keys_str_mv | AT mohammadnazarifarokhi presentingamethodtoreducethesensitivityofincrementalclusteringalgorithmsofxmldocumentsbasedoncollectiveintelligencealgorithms AT ebrahimnazarifarokhi presentingamethodtoreducethesensitivityofincrementalclusteringalgorithmsofxmldocumentsbasedoncollectiveintelligencealgorithms AT alinorouzbakhsh presentingamethodtoreducethesensitivityofincrementalclusteringalgorithmsofxmldocumentsbasedoncollectiveintelligencealgorithms |