مدل‌سازی موضوعی و کاربرد آن در پژوهش‌ها: مروری بر ادبیات تخصصی

نوع مقاله : مقالات مروری

نویسندگان

1 دانشجو/گروه علم اطلاعات و دانش شناسی، دانشگاه اصفهان، اصفهان، ایران

2 استادیار/گروه علم اطلاعات و دانش شناسی، دانشگاه اصفهان، اصفهان، ایران

3 گروه مهندسی هوش مصنوعی، دانشکده مهندسی کامپیوتر، اصفهان، ایران

چکیده

مقدمه: مدل‌سازی موضوعی یکی از تکنیک‌های متن‌کاوی است که امکان کشف موضوعات نامعلوم در مجموعه اسناد، تفسیر اسناد بر اساس این موضوعات و استفاده از این تفاسیر برای سازماندهی، خلاصه کردن و جستجوی متن‌ها را به‌طور اتوماتیک میسر می‌کند. آشنایی با مفهوم و تکنیک مدل‌سازی موضوعی، و کاربرد آن در کشف موضوعات و سازمان‌دهی منابع اطلاعاتی از اهداف اصلی این پژوهش است.
روش ­شناسی: پژوهش حاضر از نوع کتابخانه‌ای است که در آن، ضمن معرفی مدل‌سازی موضوعی، به دسته‌بندی و مرور کاربردهای این تکنیک بر اساس ماهیت عملکردی آن و ارائه نمونه تحقیقاتی که از این تکنیک استفاده نموده‌اند پرداخته است.
یافته‌ها: الگوریتم‌های مدل‌سازی موضوعی علاوه بر سه هدف اصلی مبنی بر کشف موضوعات پنهان، تفسیر اسناد بر اساس موضوعات و نهایتاً سازمان‌دهی و طبقه‌بندی متون، در کشف موضوعات و روابط پنهان در حوزه‌های علوم، بازیابی اطلاعات، دسته‌بندی مدارک بر اساس موضوعات، کشف الگوهای برجسته و رویدادهای در حال ظهور، خوشه‌بندی مفاهیم حوزه‌های علمی، تحلیل سیر تحول مفهومی در طول دوره‌های تاریخی، تعیین روابط سلسه‌مراتبی مفاهیم یک حوزه یا زمینه خاص علمی و غنی‌سازی فهرست واژگان کاربرد دارد.
نتیجه‌: مدل‌سازی موضوعی با تکیه بر یادگیری ماشین و بهره‌گیری از دانش هوش مصنوعی به‌عنوان یکی از رویکردهای نوین سازماندهی منابع اطلاعاتی مطرح شده و مطالعات جدی در این زمینه در حال انجام است. لذا با کاربرد الگوریتم‌های مدل‌سازی موضوعی در راستای خودکارسازی استخراج موضوع و کشف موضوعات نهان موجود در منبع می‌توان بر تقویت و روزآمدسازی نظام‌های نوین سازمان‌دهی منابع اطلاعاتی عمل کرد.

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