چارچوب ترکیبی (یادگیری-دانش‌محور) برای فیلتر محتوایی اطلاعات و مدیریت منابع اطلاعاتی

نوع مقاله : مقاله پژوهشی فارسی

نویسندگان

1 گروه مهندسی کامپیوتر- دانشگاه بوعلی سینا- همدان - ایران

2 گروه کامپیوتر- دانشکده مهندسی- دانشگاه بوعلی سینا- همدان- ایران

چکیده

روش‌های فیلتر محتوایی مبتنی بر دانش، روش‌های مؤثری برای جستجو، فیلتر کردن و مدیریت اطلاعات هستند. در این مقاله، یک چارچوب بدیع فیلتر و مدیریت منابع اطلاعاتی متنی معرفی می‌شود. روش پیشنهادی از دانش جمعی/گروهی مدل شده در آنتولوژی و پایگاه‌های دانش ساخت‌یافته جهت توسعه روش‌های محاسبه معنایی شباهت استفاده می‌کند. از روش‌های محاسبه معنایی شباهت توسعه داده شده برای فیلتر و دسته‌بندی کردن اسنادی استفاده می‌شود که حاوی اطلاعات متنی منطبق با ترجیحات کاربری هستند. همچنین، روش‌های توسعه داده شده در یک مدل «ترکیب خبرگان» با یکدیگر یکپارچه می‌شوند تا تصمیمات مرتبط با فیلتر و مدیریت منابع اطلاعاتی، از طریق اجتماع دانش خبره‌ها اتخاذ گردد. یکپارچه‌سازی روش‌های مبتنی بر دانش در مدل یادگیری ماشین «ترکیب خبرگان» ایده بدیع پیشنهادی در این مقاله است. نتایج ارزیابی نشان می‌دهد اجماع خبرگی روش‌های مبتنی بر دانش در مدل یادگیری گروهی «ترکیب خبرگان» عملکرد سیستم را ارتقاء می‌بخشد و منجر به دسته‌بندی دقیق اسناد متنی می‌شود.

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