کشف جوامع در شبکه‌های اجتماعی با استفاده از کاوش الگوی تکرارشونده
الموضوعات : مجله فناوری اطلاعات در طراحی مهندسیسید احمد موسوی 1 , مهرداد جلالی 2 , نگین میثاقیان 3
1 - گروه کامپیوتر
2 - دانشگاه آزاد اسلامی، مشهد
3 - گروه کامپیوتر
الکلمات المفتاحية: Social networks, شبکه‌های اجتماعی, Community Detection, کشف جامعه, کاوش الگوی تکرارشونده, Frequent pattern mining,
ملخص المقالة :
امروزه وب سایت‌های شبکه های اجتماعی به یک منبع غنی از داده های ناهمگون مبدل شده است؛ از این رو تجزیه و تحلیل این داده‌ها می‌تواند منجر به کشف اطلاعات و روابط ناشناخته در این شبکه‌ها شود. کشف جامعه متشکل از گره های مشابه یک چالش مهم در زمینه تجزیه و تحلیل داده های شبکه های اجتماعی است، و به طور گسترده ای در زمینه ساختار گرافی در این شبکه‌ها مورد مطالعه قرار گرفته است. شبکه های اجتماعی اینترنتی علاوه بر ساختار گرافی، حاوی اطلاعات مفیدی از کاربران درون شبکه می‌باشند؛ که استفاده از این اطلاعات می‌تواند منجر به بهبود کیفت کشف جوامع گردد. در این مقاله یک روش به منظور کشف جامعه ارائه شده است که علاوه بر اطلاعات ارتباطی بین گره ها از اطلاعات محتوایی به منظور ارتقا کیفیت کشف جوامع استفاده می‌گردد. این روش یک رویکرد جدید مبتنی بر الگوی تکرار شونده و بر اساس عملیات کاربران در شبکه است و به طور خاص، بر روی شبکه های اجتماعی اینترنتی که در آن کاربران عملیات مورد علاقه خود را انتخاب می کنند، اجرا می‌شود. ابتدا، بر اساس علایق و یا فعالیت های کاربران در شبکه، تعدادی جوامع کوچک متشکل از کاربران مشابه را کشف می کنیم و سپس با استفاده از ارتباطات اجتماعی هر جامعه را گسترش می دهیم. نتایج ارزیابی F-measure بر روی دو مجموعه داده دنیای واقعی (بلاگ کاتالوگ و فلیکر) نشان می‌دهد که روش پیشنهادی منجر به بهبود کیفیت کشف جوامع می شود.
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