یک الگوریتم پویای فراابتکاری برای بیشینه‌سازی نفوذ در شبکه‌های اجتماعی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکترا، گروه کامپیوتر، واحد میانه، دانشگاه آزاد اسلامی، میانه، ایران

2 استاد، گروه کامپیوتر، واحد میانه، دانشگاه آزاد اسلامی، میانه، ایران

3 استادیار، گروه کامپیوتر، واحد میانه، دانشگاه آزاد اسلامی، میانه، ایران

چکیده

در دهه گذشته، مردم زمان زیادی را در شبکه‌های اجتماعی برای تعامل با دوستان و به اشتراک گذاری اطلاعات، افکار، اخبار و غیره صرف می‌کنند. این شبکه‌های اجتماعی بخش مهمی از زندگی روزمره ما را تشکیل می‌دهند. با بهره‌برداری از توسعه شبکه‌های اجتماعی، یافتن افراد تأثیرگذار در یک شبکه‌ی اجتماعی کاربردهای عملی زیادی در بازاریابی، سیاست و حتی کنترل بیماری‌ها دارد. در این مقاله، روش جدیدی‌ با عنوان الگوریتم کرکس توسعه‌یافته پویا برای حل مسئله بیشینه‌سازی نفوذ ارائه کرده‌ایم. با توجه به این نکته که در دنیای واقعی، شبکه‌های اجتماعی ماهیت بسیار پویا و مقیاس‌پذیر دارند. در الگوریتم پیشنهادی ما دو معیار مهم که در کارهای انجام شده قبلی کمتر مورد توجه قرار گرفته است را در نظر می‌گیریم. یکی تغییر ساختار شبکه در طول زمان و دیگری مقیاس‌پذیری است. الگوریتم پیشنهادی روی مجموعه داده‌های استاندارد مورد ارزیابی قرارگرفته شده است. نتایج به دست آمده نشان می‌دهد که الگوریتم پیشنهادی به دلیل کاهش فضای جستجو و استفاده از چندین مکانیسم مختلف و متفاوت در مراحل اکتشاف و بهره‌وری و ایجاد تعادل و گذار بین این مراحل نسبت به دیگر الگوریتم‌های مورد مقایسه، مقیاس‌پذیرتر بوده و از دقت بالاتری در پیدا کردن رئوس بانفوذ در این شبکه‌ها را برخوردار است.

کلیدواژه‌ها


عنوان مقاله [English]

A Dynamic Metaheuristic Algorithm for Influence Maximization in Social Networks

نویسندگان [English]

  • Jalil Jabbari Lotf 1
  • Mohammad Abdollahi Azgomi 2
  • Mohammad Reza Ebrahimi Dishabi 3
1 Ph.D. student, Computer Department, Miyaneh Branch, Islamic Azad University, Miyaneh, Iran
2 Professor, Computer Department, Miyaneh Branch, Islamic Azad University, Miyaneh, Iran
3 Assistant Professor, Computer Department, Miyaneh Branch, Islamic Azad University, Miyaneh, Iran
چکیده [English]

During the very last decade, people have been spending lots of time working with social networks to interact with friends and to share information, thoughts, news, and etc. These social networks comprise a very important part of our daily lives. Along with the exploitation of the development of social networks, finding influential individuals in a social network has many practical functions in marketing, politics, and even control of the diseases. In the present research, a novel method called the dynamic generalized vulture algorithm has been proposed to solve influence maximization problems. Regarding the fact that in real world social networks own very dynamic and scalable nature, through our proposed algorithm, we have considered two important criteria which have been rarely taken into consideration in previous projects. The first criterion is due to the network structure change during time pass and the other refers to scalability. The suggested algorithm was measured considering standard data sets. The results showed that the proposed algorithm has been more scalable and has had higher precision in locating the most influential tops in such networks compared with other algorithms due to the reduction of search area and using several different mechanisms during navigation and optimization, balance creation and moving through these stages.

کلیدواژه‌ها [English]

  • Influence maximization
  • Social networks
  • Network dynamicity
  • Diffusion model
  • metaheuristic algorithms

Smiley face

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دوره 11، شماره 2 - شماره پیاپی 42
شماره پیاپی 42، فصلنامه تابستان
تیر 1402
صفحه 57-69
  • تاریخ دریافت: 11 مرداد 1401
  • تاریخ بازنگری: 08 بهمن 1401
  • تاریخ پذیرش: 10 بهمن 1401
  • تاریخ انتشار: 01 تیر 1402