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الرئيسية > Maximal Assortative Matching f...>الوصف

Maximal Assortative Matching for Complex Network Graphs

المصدر: مجلة جامعة الملك سعود - علوم الحاسب والمعلومات
الناشر: جامعة الملك سعود
المؤلف الرئيسي: Meghanathan, Natarajan (Author)
المجلد/العدد: مج28, ع2
محكمة: نعم
الدولة: السعودية
التاريخ الميلادي: 2016
الصفحات: 230 - 246
DOI: 10.33948/0584-028-002-007
ISSN: 1319-1578
رقم MD: 973886
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: science
مواضيع:
الخوارزميات | الرسوم البيانية | شبكات التواصل الاجتماعي
كلمات المؤلف المفتاحية:
Maximal Matching | Assortative Matching | Dissortative Matching | Assortativity Index | Complex Networks | Node Similarity
رابط المحتوى:
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المستخلص: We define the problem of maximal assortativity matching (MAM) for a complex network graph as the problem of maximizing the similarity of the end vertices (with respect to some measure of node weight) constituting the matching. In this pursuit, we introduce a metric called the assortativity weight of an edge, defined as the product of the number of uncovered adjacent edges and the absolute value of the difference in the weights of the end vertices. The MAM algorithm prefers to include edges that have the smallest assortativity weight in each iteration (one edge per iteration) until all edges are covered. The MAM algorithm can also be adapted to determine a maximal dissortative matching (MDM) to maximize the dissimilarity between the end vertices that are part of a matching as well as to determine a maximal node matching (MNM) that simply maximizes the number of vertices that are part of the matching. We run the MAM, MNM and MDM algorithms on real-world network graphs as well as on the theoretical model-based random network graphs and scale-free network graphs and analyze the tradeoffs between the % of node matches and assortativity index (targeted optimal values: 1 for MAM and _1 for MDM).
ISSN: 1319-1578

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