روشی نوین برای پیش‌بینی ارتباط در شبکه‌های اجتماعی ناهمگن
الموضوعات :سعیده رضاوندی شعاعی 1 , هادی زارع 2
1 - دانشگاه تهران
2 - دانشگاه تهران
الکلمات المفتاحية: اندازه شباهت پیش‌بینی ارتباط شبکه‌های اجتماعی شبکه‌های اجتماعی ناهمگن کاوش ارتباطات یادگیری با ناظر,
ملخص المقالة :
با گسترش روزافزون شبکه‌های اجتماعی، علوم شبکه مورد توجه بسیاری از پژوهشگران در زمینه‌های مختلف قرار گرفته است. علاوه بر آن بسیاری از مسایل کاربردی مهندسی با استفاده از ابزار شبکه‌های اجتماعی مدل‌سازی شده‌اند. پیش‌بینی تغییر و تحول در ساختار شبکه‌های اجتماعی یکی از مسایل اساسی در تحلیل شبکه‌های اجتماعی است که با عنوان مسأله پیش‌بینی ارتباط در علوم شبکه شناخته می‌شود. امروزه با گسترش استفاده از شبکه‌های اجتماعی، فعالیت افراد در قالب چندین شبکه با عنوان شبکه‌های اجتماعی ناهمگن رواج پیدا کرده است. پیش‌بینی ارتباط در شبکه‌های اجتماعی ناهمگن را می‌توان بر اساس اطلاعات اضافی موجود نسبت به روش‌های قبلی مورد بهبود قرار داد. در رویکرد پیشنهادی این مقاله، ابتدا یک معیار شباهت جدید برای کاربران در شبکه‌های ناهمگن بر اساس توسعه روش‌های مطرح پیشین و با در نظر گرفتن ارتباط بین لایه‌های مختلف معرفی می‌شود، سپس با استفاده از رویکرد یادگیری باناظر و بهره‌گیری از ویژگی‌های تولیدشده بر مبنای معیار شباهت معرفی‌شده، الگوریتم پیشنهادی مورد تشریح قرار می‌گیرد. برای ارزیابی روش پیشنهادی از معیارهای استاندارد همانند دقت و صحت بهره گرفته‌ایم. مقایسه روش پیشنهادی با روش‌های شناخته‌شده پیشین بر روی مجموعه داده‌های مختلف نشان می‌دهد که روش پیشنهادی ما برای پیش‌بینی ارتباط از عملکرد بهتر و مطلوب‌تری برخوردار است به طوری که از نظر صحت تا ۲۰ درصد موجب بهبود عملکرد شده است.
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