دوره 19، شماره 1 - ( 3-1401 )                   جلد 19 شماره 1 صفحات 18-1 | برگشت به فهرست نسخه ها

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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) :1-18
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) :18-1

URL: http://jsdp.rcisp.ac.ir/article-1-1199-fa.html


دانشگاه آزاد اسلامی واحد نورآباد ممسنی، فارس، ایران
چکیده:   (357 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
متن کامل [PDF 1358 kb]   (126 دریافت)    
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

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