Advances in document clustering with evolutionary-based algorithms
Document clustering is the process of organizing a particularelectronic corpus of documents into subgroups of similar text features.Formerly, a number of conventional algorithms had been applied to performdocument clustering. There are current endeavors to enhance clusteringperformance by employing...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Science Publications
2015
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| Online Access: | http://psasir.upm.edu.my/id/eprint/43671/1/Advances%20in%20Document%20Clustering%20with%20Evolutionary-Based.pdf |
| _version_ | 1825929410754117632 |
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| author | Makki, Sarmad Yaakob, Razali Mustapha, Norwati Ibrahim, Hamidah |
| author_facet | Makki, Sarmad Yaakob, Razali Mustapha, Norwati Ibrahim, Hamidah |
| author_sort | Makki, Sarmad |
| collection | UPM |
| description | Document clustering is the process of organizing a particularelectronic corpus of documents into subgroups of similar text features.Formerly, a number of conventional algorithms had been applied to performdocument clustering. There are current endeavors to enhance clusteringperformance by employing evolutionary algorithms. Thus, such endeavors becamean emerging topic gaining more attention in recent years. The aim of this paperis to present an up-to-date and self-contained review fully devoted to documentclustering via evolutionary algorithms. Itfirstly provides a comprehensive inspection to the document clustering model revealingits various components with its related concepts. Then it shows and analyzesthe principle research work in this topic. Finally, it compiles and classifiesvarious objective functions, the core of the evolutionary algorithms, from therelated collection of research papers. The paper ends up by addressing someimportant issues and challenges that can be subject of future work. |
| first_indexed | 2024-03-06T08:56:21Z |
| format | Article |
| id | upm.eprints-43671 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T08:56:21Z |
| publishDate | 2015 |
| publisher | Science Publications |
| record_format | dspace |
| spelling | upm.eprints-436712017-11-29T02:57:25Z http://psasir.upm.edu.my/id/eprint/43671/ Advances in document clustering with evolutionary-based algorithms Makki, Sarmad Yaakob, Razali Mustapha, Norwati Ibrahim, Hamidah Document clustering is the process of organizing a particularelectronic corpus of documents into subgroups of similar text features.Formerly, a number of conventional algorithms had been applied to performdocument clustering. There are current endeavors to enhance clusteringperformance by employing evolutionary algorithms. Thus, such endeavors becamean emerging topic gaining more attention in recent years. The aim of this paperis to present an up-to-date and self-contained review fully devoted to documentclustering via evolutionary algorithms. Itfirstly provides a comprehensive inspection to the document clustering model revealingits various components with its related concepts. Then it shows and analyzesthe principle research work in this topic. Finally, it compiles and classifiesvarious objective functions, the core of the evolutionary algorithms, from therelated collection of research papers. The paper ends up by addressing someimportant issues and challenges that can be subject of future work. Science Publications 2015 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/43671/1/Advances%20in%20Document%20Clustering%20with%20Evolutionary-Based.pdf Makki, Sarmad and Yaakob, Razali and Mustapha, Norwati and Ibrahim, Hamidah (2015) Advances in document clustering with evolutionary-based algorithms. American Journal of Applied Sciences, 12 (10). pp. 689-708. ISSN 1546-9239; ESSN: 1554-3641 http://thescipub.com/abstract/10.3844/ajassp.2015.689.708 10.3844/ajassp.2015.689.708 |
| spellingShingle | Makki, Sarmad Yaakob, Razali Mustapha, Norwati Ibrahim, Hamidah Advances in document clustering with evolutionary-based algorithms |
| title | Advances in document clustering with evolutionary-based algorithms |
| title_full | Advances in document clustering with evolutionary-based algorithms |
| title_fullStr | Advances in document clustering with evolutionary-based algorithms |
| title_full_unstemmed | Advances in document clustering with evolutionary-based algorithms |
| title_short | Advances in document clustering with evolutionary-based algorithms |
| title_sort | advances in document clustering with evolutionary based algorithms |
| url | http://psasir.upm.edu.my/id/eprint/43671/1/Advances%20in%20Document%20Clustering%20with%20Evolutionary-Based.pdf |
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