A survey of recommender systems with multi-objective optimization
Recommender systems have been widely applied to several domains and applications to
assist decision making by recommending items tailored to user preferences. One of the …
assist decision making by recommending items tailored to user preferences. One of the …
[HTML][HTML] Economic recommender systems–a systematic review
Many of today's online services provide personalized recommendations to their users. Such
recommendations are typically designed to serve certain user needs, eg, to quickly find …
recommendations are typically designed to serve certain user needs, eg, to quickly find …
A deep learning based algorithm for multi-criteria recommender systems
Q Shambour - Knowledge-based systems, 2021 - Elsevier
Recommender systems have become exceptionally widespread in recent years to deal with
the information overload problem by providing personalized recommendations. Multi-criteria …
the information overload problem by providing personalized recommendations. Multi-criteria …
A novel group recommender system for domain-independent decision support customizing a grou** genetic algorithm
Group formation is a complex task requiring computational support to succeed. In the
literature, there has been considerable effort in the development of algorithms for composing …
literature, there has been considerable effort in the development of algorithms for composing …
Integrating contextual sentiment analysis in collaborative recommender systems
Recently. recommender systems have become a very crucial application in the online
market and e-commerce as users are often astounded by choices and preferences and they …
market and e-commerce as users are often astounded by choices and preferences and they …
DNN-MF: Deep neural network matrix factorization approach for filtering information in multi-criteria recommender systems
Personalization systems have proved to be one of the most powerful tools for e-commerce
sites, assisting users in discovering the most relevant products across enormous product …
sites, assisting users in discovering the most relevant products across enormous product …
Path-based recommender system for learning activities using knowledge graphs
Recommender systems can offer a fertile ground in e-learning software, since they can
assist users by presenting them with learning material in which they can be more interested …
assist users by presenting them with learning material in which they can be more interested …
Unsupervised semantic approach of aspect-based sentiment analysis for large-scale user reviews
Aspect-based sentiment analysis (ABSA) has recently attracted increasing attention due to
its extensive applications. Most of the existing ABSA methods been applied on small-sized …
its extensive applications. Most of the existing ABSA methods been applied on small-sized …
Multi-criteria ranking: Next generation of multi-criteria recommendation framework
Recommender systems have been developed to assist decision making by recommending a
list of items to the end users. The multi-criteria recommender system (MCRS) is a special …
list of items to the end users. The multi-criteria recommender system (MCRS) is a special …
Membangun Sistem Rekomendasi Hotel dengan Content Based Filtering Menggunakan K-Nearest Neighbor dan Haversine Formula
Peningkatakan pertumbuhan industri hotel pada tiap tahunnya dan preferensi konsumen
yang bervariasi dalam kebutuhan layanan hotel mengakibatkan konsumen lebih konsumtif …
yang bervariasi dalam kebutuhan layanan hotel mengakibatkan konsumen lebih konsumtif …