تشخیص همزمان زیرگراف های فشرده ناهنجار در شبکه های اجتماعی بزرگ

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد گروه مهندسی کامپیوتر، دانشکده فنی مهندسی، دانشگاه شاهد، تهران، ایران

2 هیات علمی دانشکده فنی مهندسی دانشگاه شاهد

چکیده

این مقاله رویکرد جدید تشخیص ناهنجاری بدون علامت براساس پردازش سیگنال های مرتبط با اطلاعات محلی ارایه می دهد که قادر به تعیین همزمان زیرگراف های فشرده ناهنجار در گراف ناشناخته نویزی شبکه های اجتماعی بزرگ است. همچنین الگوریتم جدید نمونه برداری مبتنی بر نمونه برداری فشرده جهت بازیابی ویژگی های تنک شبکه های ثابت ارایه داده که هدفش بهبود دقتِ تشخیص ناهنجاری همراه با کاهش پیچیدگیِ نمونه برداری داده ها است. نتایج آزمایشات تجربی با داده های مصنوعی و واقعی شبکه های اجتماعی ‌در مقایسه با مهم ترین روش های علمی نشان داد که رویکرد پیشنهادی علاوه بر برخورداری از دقت تشخیص همزمان چندین زیرگراف فشرده، پیچیدگی محاسباتی را از O(n^4 √(log⁡n )) به O(n^2) در شبکه n گره ای کاهش داده و به آسانی قابل کاربرد در شبکه های پویای پیچیده است.

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