Feature Selection And Enhanced Krill Herd Algorithm For Text Document Clustering
Text document (TD) clustering is a new trend in text mining in which the TDs are separated into several coherent clusters, where documents in the same cluster are similar. In this study, a new method for solving the TD clustering problem worked in the following two stages: (i) A new feature selecti...
محفوظ في:
المؤلف الرئيسي: | |
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التنسيق: | أطروحة |
اللغة: | English |
منشور في: |
2018
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الموضوعات: | |
الوصول للمادة أونلاين: | http://eprints.usm.my/43662/1/LAITH%20MOHAMMAD%20QASIM%20ABUALIGAH.pdf |
الوسوم: |
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الملخص: | Text document (TD) clustering is a new trend in text mining in which the TDs are separated into several coherent clusters, where documents in the same cluster are
similar. In this study, a new method for solving the TD clustering problem worked in the following two stages: (i) A new feature selection method using particle swarm
optimization algorithm with a novel weighting scheme and a detailed dimension reduction technique are proposed to obtain a new subset of more informative features with low-dimensional space. |
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