تولید توضیح شخصی سازی شده برای سیستم پیشنهاددهنده لیست توئیتر مبتنی بر شباهت معنایی هشتگ ها
الموضوعات :حوا علیزاده نوقابی 1 , بهشید بهکمال 2 , صالحه ناصری 3 , محسن کاهانی 4
1 - گروه مهندسی کامپیوتر، دانشگاه فردوسی مشهد
2 - عضو هیات علمی
3 - گروه مهندسی کامپیوتر، دانشگاه فردوسی مشهد
4 - استاد
الکلمات المفتاحية: سیستم های پیشنهاددهنده توضیح پذیر, توضیح شخصی سازی شده, لیست توئیتر, شباهت معنایی هشتگ ها,
ملخص المقالة :
امروزه سیستم‌های پشنهاددهنده ی لیست های توئیتر با بکارگیری اطلاعات مختلف کاربران و لیستها و همچنین اعمال الگوریتمهای پیچیده، توانسته اند به دقت بالایی در پیش بینی برسند و پیشنهادهای مرتبط با هر کاربر را تولید کنند، اما قابلیت توضیح پذیری در این سیستم ها به عنوان یک چالش مطرح می باشد. توضیح مناسب به همراه یک لیست پیشنهادشده علاوه بر افزایش اعتماد و رضایت کاربران، می تواند به آنها در تصمیم‌گیری آگاهانه کمک نماید. از این رو در این مقاله، یک مدل تولید توضیح ارائه میشود که به ایجاد خودکار یک توصیف برای لیست پیشنهادشده بصورت شخصی سازی شده برای کاربر مدنظر می پردازد. بطور دقیقتر، این مدل با انتخاب هشتگهای پرتکرار از محتوای لیست که ارتباط معنایی با تاریخچه فعالیت های قبلی کاربر دارد، سعی میکند موضوع لیست را به گونهای قابل درک و شخصی سازی شده در قالب یک توضیح همراه با لیست پیشنهادشده نمایش دهد. پس از جمع آوری یک مجموعه داده واقعی از شبکه توئیتر، با انجام آزمایش‌ها نشان داده شد که مدل پیشنهادی قادر به تولید توضیح برای درصد بالایی از پیشنهادهای ایجادشده براساس یک مدل پیشنهاددهنده پایه میب اشد.
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