ارائه سیستم جدید توصیه عادلانه گروهی مبتنی بر تأثیر اعضا و رهبر

نوع مقاله : مقاله کامپیوتر

نویسندگان

1 استادیار، گروه مهندسی کامپیوتر، دانشگاه صنعتی بیرجند، بیرجند، ایران

2 کارشناس ارشد، گروه مهندسی کامپیوتر، دانشگاه آزاد اسلامی، واحد بیرجند، بیرجند، ایران

چکیده

در یک سیستم توصیه­گر گروهی تلاش می­شود ارائه توصیه به گروهی از افراد به‌جای یک فرد صورت پذیرد. در این سیستم­ها نظرات تمام اعضای گروه در تصمیم‏گیری مؤثر بوده و سعی می­شود تا باوجود متفاوت بودن ترجیحات شخصی، بهترین انتخاب فراهم آید. این مقاله، سعی در ارائه یک سیستم توصیه­گر گروهی دارد که بتواند ارتباط بین کاربران و درنهایت تأثیر هر کاربر بر گروه را مشخص کرده و سپس با توجه به این ارتباطات، بهترین توصیه را به پیشنهاد دهد. همچنین، معیاری جدید برای تعیین رهبر در گروه تعیین می‌شود که با توجه به میزان اعتماد، شباهت و تعلق و وابستگی کاربران به گروه، رهبر آن گروه را مشخص نماید. بعلاوه، معیار جدیدی برای ارائه توصیه عادلانه به گروه ارائه‌شده که با استفاده از آن آیتم­هایی به کاربران توصیه شود که بیشترین نظر مثبت در بین همه اعضا گروه داشته باشد. الگوریتم پیشنهادی در دو بخش با الگوریتم­های مشابه در این زمینه، مقایسه شده است. در بخش ارزیابی رتبه‌های تعیین شده، دقت روش پیشنهادی در همه حالات نزدیک به 100% به دست آمد که به نسبت روش‌های مورد مقایسه به طور متوسط بهبود 5 درصدی را گزارش نمود. در بخش ارزیابی توصیه‌ها نیز از معیارهای شناخته شده  nDCG، رضایت گروهی و عدالت استفاده شد که روش پیشنهادی با در نظر گرفتن تعداد توصیه‌های مختلف به طور متوسط در هریک از معیارهای ذکر شده در حالت میانگین به ترتیب 41%، 35% و 38% بهبود یافته است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

A Fair Group Recommendation System Based on Members and Leader Influences

نویسندگان [English]

  • Mostafa Sabzekar 1
  • Bentolhoda Moazeni 2
1 Assistant Professor, Department of Computer Engineering, Birjand University of Technology, Birjand, Iran
2 MSc, Department of Computer Engineering, Islamic Azad University, Birjand Branch, Birjand, Iran
چکیده [English]

In a group recommender system, the effort is made to provide recommendations to a group of individuals rather than a single person. In these systems, the opinions of all group members are influential in decision-making, aiming to provide the best choice despite different personal preferences. This article attempts to present a group recommender system capable of identifying the relationship among users and eventually determining the influence of each user on the group, subsequently offering the best recommendations based on these connections. Moreover, a new criterion for determining leadership in the group is introduced, which identifies the leader of the group based on the level of trust, similarity, belongingness, and dependence of users on the group. Additionally, a novel criterion for delivering fair recommendations to the group is proposed, suggesting items to users with the most positive feedback among all group members. The proposed algorithm is compared with similar algorithms in this domain in two sections. In the evaluation section of assigned rankings, the accuracy of the proposed method was close to 100% in all cases, reporting an average improvement of 5% compared to the compared methods. In the recommendation evaluation section, well-known criteria such as nDCG, group satisfaction, and fairness were used, where the proposed method showed an average improvement of 41%, 35%, and 38%, respectively, considering the number of diverse recommendations in each of the mentioned criteria on average.

کلیدواژه‌ها [English]

  • Group recommender systems
  • Fairness
  • Aggregation function

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مدل سازی در مهندسی
دوره 22، شماره 77
شهریور 1403
صفحه 221-243

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  • تاریخ دریافت: 10 مرداد 1402
  • تاریخ بازنگری: 18 آذر 1402
  • تاریخ پذیرش: 22 آذر 1402

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