این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
مدیریت فناوری اطلاعات، جلد ۱۱، شماره ۲، صفحات ۵۹-۷۸
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی A Grouping Hotel Recommender System Based on Deep Learning and Sentiment Analysis
چکیده انگلیسی مقاله Recommender systems are important tools for users to identify their preferred items and for businesses to improve their products and services. In recent years, the use of online services for selection and reservation of hotels have witnessed a booming growth. Customer' reviews have replaced the word of mouth marketing, but searching hotels based on user priorities is more time-consuming. This study is aimed at designing a recommender system based on the explicit and implicit preferences of the customers in order to increase prediction's accuracy. In this study, we have combined sentiment analysis with the Collaborative Filtering (CF) based on deep learning for user groups in order to increase system accuracy. The proposed system uses Natural Language Processing (NLP) and supervised classification approach to analyze sentiments and extract implicit features. In order to design the recommender system, the Singular Value Decomposition (SVD) was used to improve scalability. The results show that our proposed method improves CF performance.
کلیدواژه‌های انگلیسی مقاله
نویسندگان مقاله Fatemeh Abbasi |
Postdoctoral researcher, Department of Social and Economic, Alzahra University, Tehran, Iran.

Ameneh Khadivar |
Associate Professor, Department of Social and Economic, Alzahra University, Tehran, Iran.

Mohsen Yazdinejad |
Ph.D. Student, Faculty of Computing Engineering, University of Isfahan , Iran.

نشانی اینترنتی https://jitm.ut.ac.ir/article_73948_eac728ff5cdfbea6a1a002dcfcd48575.pdf
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات