دوره 19، شماره 1 - ( 3-1401 )
جلد 19 شماره 1 صفحات 18-1 |
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bahrani P, Minaei Bidgoli B, Parvin H, Mirzarezaee M, Keshavarz A. An Ontological Hybrid Recommender System for Dealing with Cold Start Problem. JSDP 2022; 19 (1) : 1
URL: http://jsdp.rcisp.ac.ir/article-1-1199-fa.html
URL: http://jsdp.rcisp.ac.ir/article-1-1199-fa.html
بحرانی پیام، مینایی بیدگلی بهروز، پروین حمید، میرزارضایی میترا، کشاورز احمد. سامانه پیشنهادگر ترکیبی، مبتنی بر هستانشناسی برای مقابله با مشکل شروع سرد. پردازش علائم و داده‌ها. 1401; 19 (1) :1-18
دانشگاه آزاد اسلامی واحد نورآباد ممسنی، فارس، ایران
چکیده: (1535 مشاهده)
انتظار می‌رود سامانه‌های پیشنهادگر (RS) قلم‌های دقیق را به مصرف‌کنندگان پیشنهاد دهند. شروع سرد مهم‌ترین چالش در RSها است. RSهای ترکیبی اخیر، دو مدل پالایش محتوا پایه (ConF)و پالایش مشارکتی (ColF) را با هم ترکیب می‌کنند. در این پژوهش، یک RS ترکیبی مبتنی بر هستانشناسی معرفی می‌شود که در آن هستانشناسی در بخش ConF به‌کار رفته است، این در حالی است که ساختار هستانشناسی توسط بخش ColF بهبود داده می‌شود. در این مقاله، رویکرد ترکیبی جدیدی مبتنی بر ترکیب شباهت جمعیت‌شناختی و شباهت کسینوسی بین کاربران به‌منظور حل مشکل شروع سرد از نوع کاربر جدید، ارائه شده است. همچنین، رویکرد جدیدی مبتنی بر ترکیب شباهت هستانشناسی و شباهت کسینوسی بین اقلام به‌منظور حل مسأله شروع سرد از نوع قلم جدید، ارائه شده است. ایده اصلی روش پیشنهادی، گسترش پروفایل‌های کاربر/قلم بر اساس سازوکارهای مختلف برای ایجاد پروفایل با عملکرد بالاتر برای کاربران/قلم‌ها است. روش پیشنهادی در یک مجموعه‌داده واقعی ارزیابی شده است و آزمایش‌ها نشان می‌دهند که روش پیشنهادی در مقایسه با روش‌های پیشرفتهRS ، به‌خصوص در مواجهه با مسأله شروع سرد، عملکرد بهتری دارد.
شماره‌ی مقاله: 1
نوع مطالعه: پژوهشي |
موضوع مقاله:
مقالات پردازش داده‌های رقمی
دریافت: 1399/9/26 | پذیرش: 1400/3/1 | انتشار: 1401/4/1 | انتشار الکترونیک: 1401/4/1
دریافت: 1399/9/26 | پذیرش: 1400/3/1 | انتشار: 1401/4/1 | انتشار الکترونیک: 1401/4/1
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