طبقه‌بندی گره‌ها در گراف‌های استنادی با استفاده از شبکه‌های عصبی گراف

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد، دانشگاه جامع امام حسین (ع)، تهران، ایران

2 دانشجوی دکتری، دانشگاه جامع امام حسین (ع)، تهران، ایران

3 استادیار، دانشگاه جامع امام حسین (ع)، تهران، ایران

چکیده

گراف‌ها، داده‌هایی هستند که روابط پیچیده بین موارد مختلفی مانند اینترنت، شبکه اجتماعی، شبکه کتابشناختی و مانند آن را در دنیای واقعی توصیف می‌کنند. یکی از مواردی که امروزه افراد بسیاری با آن سر و کار دارند، شبکه‌های اجتماعی آنلاین می‌باشد. نمایش گراف شبکه‌های اجتماعی آنلاین نظیر توییتر، وی چت و فیس بوک امروزه با کمتر از میلیاردها گره امکان‌پذیر نمی‌باشد و من باب همین موضوع، مطالعه داده‌های شبکه در مقیاس بزرگ برای محققان را به یک امر ضروری تبدیل کرده است. در مورد شبکه‌های اجتماعی، کاربران آنلاین اغلب اطلاعات محدودی دارند؛ اما برای ارائه‌دهندگان خدمات رسانه‌های اجتماعی، اطلاعات گره کاربر مانند علاقه، اعتقادات یا ویژگی‌های دیگر برای سفارشی کردن خدمات آن‌ها برای کاربران در بسیاری از برنامه‌ها مانند توصیه‌ها و جستجوی شخصی بسیار مهم است و آن را به یک چالش برای ارائه‌دهندگان خدمات تبدیل کرده است. یک راه مؤثر برای مقابله با این چالش، استنتاج اطلاعات گمشده کاربر با استفاده از ساختارهای شبکه‌ای فراگیر در رسانه‌های اجتماعی است. یکی از مهم‌ترین استنتاج‌ها در داده‌کاوی و تحلیل شبکه، طبقه‌بندی گره‌ها است که هدف آن استنتاج برچسب‌های گمشده گره‌ها بر اساس گره‌های برچسب‌گذاری شده و ساختار شبکه است. در این پژوهش وظیفه طبقه‌بندی گره‌ها بر روی مجموعه داده‌های شبکه استنادی PubMedDiabetes، CiteSeer و Cora با استفاده از شبکه‌های عصبی گراف GraphSAGE، GCN و GAT مورد بررسی قرار داده شده است و به صورت کلی نتیجه حاصل شده است که شبکه عصبی گراف GraphSAGE بر روی مجموعه داده‌های شبکه استنادی ذکرشده برای وظیفه طبقه‌بندی گره‌ها به خوبی عمل می‌کند.

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مقالات آماده انتشار، پذیرفته شده
انتشار آنلاین از تاریخ 01 خرداد 1403
  • تاریخ دریافت: 05 دی 1402
  • تاریخ بازنگری: 25 فروردین 1403
  • تاریخ پذیرش: 14 اردیبهشت 1403
  • تاریخ انتشار: 01 خرداد 1403