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الرئيسية > Arabic Web Page Clustering: A...>الوصف

Arabic Web Page Clustering: A Review

المصدر: مجلة جامعة الملك سعود - علوم الحاسب والمعلومات
الناشر: جامعة الملك سعود
المؤلف الرئيسي: Alghamdi, Hanan M. (Author)
مؤلفين آخرين: Selamat, Ali (Co-Author)
المجلد/العدد: مج31, ع1
محكمة: نعم
الدولة: السعودية
التاريخ الميلادي: 2019
الصفحات: 1 - 14
DOI: 10.33948/0584-031-001-001
ISSN: 1319-1578
رقم MD: 974516
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: science
مواضيع:
تكنولوجيا المعلومات | صفحات الويب | اللغة العربية
كلمات المؤلف المفتاحية:
Feature Selection | Feature Reduction | K-Means | Review | Text Clustering | Arabic Web Page
رابط المحتوى:
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المستخلص: Clustering is the method employed to group Web pages containing related information into clusters, which facilitates the allocation of relevant information. Clustering performance is mostly dependent on the text features’ characteristics. The Arabic language has a complex morphology and is highly inflected. Thus, selecting appropriate features affects clustering performance positively. Many studies have addressed the clustering problem in Web pages with Arabic content. There are three main challenges in applying text clustering to Arabic Web page content. The first challenge concerns difficulty with identifying significant term features to represent original content by considering the hidden knowledge. The second challenge is related to reducing data dimensionality without losing essential information. The third challenge regards how to design a suitable model for clustering Arabic text that is capable of improving clustering performance. This paper presents an overview of existing Arabic Web page clustering methods, with the goals of clarifying existing problems and examining feature selection and reduction techniques for solving clustering difficulties. In line with the objectives and scope of this study, the present research is a joint effort to improve feature selection and victimization frameworks in order to enhance current text analysis techniques that can be applied to Arabic Web pages. © 2017 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
ISSN: 1319-1578

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