ارائه یک سامانه پیشنهادگر حافظه پایه ترکیبی با استفاده از هستان‌شناسی و محتوا

بحرانی, پیام; مینایی بیدگلی, بهروز; پروین, حمید; میرزارضایی, میترا; کشاورز, احمد

doi:10.52547/jsdp.18.4.89

دوره 18، شماره 4 - ( 12-1400 ) جلد 18 شماره 4 صفحات 124-89 | برگشت به فهرست نسخه ها

‎ 10.52547/jsdp.18.4.89

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Minaei2 B, Parvin H, Mirzarezaee M, Keshavarz A. A New WordNet Enriched Content-Collaborative Recommender System. JSDP 2022; 18 (4) : 7
URL: http://jsdp.rcisp.ac.ir/article-1-1185-fa.html

بحرانی پیام، مینایی بیدگلی بهروز، پروین حمید، میرزارضایی میترا، کشاورز احمد. ارائه یک سامانه پیشنهادگر حافظه پایه ترکیبی با استفاده از هستان‌شناسی و محتوا. پردازش علائم و داده‌ها. 1400; 18 (4) :89-124

URL: http://jsdp.rcisp.ac.ir/article-1-1185-fa.html

ارائه یک سامانه پیشنهادگر حافظه پایه ترکیبی با استفاده از هستان‌شناسی و محتوا

پیام بحرانی، بهروز مینایی بیدگلی

، حمید پروین^*

، میترا میرزارضایی

، احمد کشاورز

گروه مهندسی کامپیوتر، واحد نورآباد ممسنی، دانشگاه آزاد اسلامی

چکیده: (2157 مشاهده)

سامانه‌های پیشنهادگر در زمینه تجارت الکترونیک شناخته شده هستند. از این‌گونه سیستم‌ها انتظار می‌رود که کالاها و اقلام مهمی (از جمله موسیقی و فیلم) را به مشتریان پیشنهاد دهند. در سامانه‌های پیشنهادگر سنتی از جمله روشهای پالایش محتوا پایه و پالایش مشارکتی، چالش‌ها و مشکلات مهمی از جمله شروع سرد، مقیاس‌پذیری و پراکندگی داده‌ها وجود دارد. اخیراً به‌کارگیری روش‌های ترکیبی توانسته با بهره‌گیری از مزایای این روش‌ها با هم، برخی از این چالش‌ها را تا حد قابل قبولی حل نمایند. در این مقاله سعی می‌شود روشی برای پیشنهاد ارائه شود که ترکیبی از دو روش پالایش محتوا پایه و پالایش مشارکتی (شامل دو رویکرد حافظه پایه و مدل پایه) باشد. روش پالایش مشارکتی حافظه پایه، دقت بالایی دارد، اما از مقیاس‌پذیری کمی برخوردار است. در مقابل، رویکرد مدل پایه دارای دقت کمی در ارائه پیشنهاد به کاربران بوده اما مقیاس‌پذیری بالایی از خود نشان می‌دهد. در این مقاله سامانه پیشنهادگر ترکیبی مبتنی بر هستان‌شناسی ارائه شده که از مزایای هر دو روش بهره برده و براساس رتبه‌بندی‌های واقعی، مورد ارزیابی قرار می‌گیرد. هستان‌شناسی، توصیفی واضح و رسمی برای تعریف یک پایگاه دانش شامل مفاهیم (کلاس‌ها) در حوزه موضوعی، نقش‌ها (رابط‌ها) بین نمونه‌های مفاهیم، محدودیت‌های مربوط به رابطه‌ها، همراه با یک مجموعه از عناصر و اعضا (یا نمونه‌ها) است که یک پایگاه دانش را تعریف می‌کند. هستان‌شناسی در بخش پالایش محتوا پایه مورد استفاده قرار می‌گیرد و ساختار هستان‌شناسی توسط تکنیک‌های پالایش مشارکتی بهبود می‌یابد. در روش ارائه‌شده در این پژوهش، عملکرد سیستم پیشنهادی بهتر از عملکرد پالایش محتوا پایه و مشارکتی است. روش پیشنهادی با استفاده از یک مجموعه‌داده واقعی ارزیابی شده است و نتایج آزمایشها نشان می‌دهد روش مذکور کارایی بهتری دارد. همچنین با توجه به راه‌کارهای ارائه‌شده در مقاله حاضر، مشخص شد، روش پیشنهادی دقت و مقیاس‌پذیری مناسبی نسبت به سامانه‌های پیشنهادگری دارد که صرفاً حافظه پایه (KNN) و یا مدل پایه هستند.

شماره‌ی مقاله: 7

واژه‌های کلیدی: سامانه پیشنهادگر، هستان‌شناسی، پالایش حافظه پایه، پالایش مدل پایه، خوشه‌بندی، KNN

متن کامل [PDF 3065 kb] (793 دریافت)

نوع مطالعه: پژوهشي | موضوع مقاله: مقالات پردازش داده‌های رقمی
دریافت: 1399/8/4 | پذیرش: 1399/12/18 | انتشار: 1401/1/1 | انتشار الکترونیک: 1401/1/1

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