The recommender systems are recently becoming more significant in the age of rapid
development of the Internet technology due to their ability in making a decision to users on …

Modern companies generate value by digitalizing their services and products. Knowing what
customers are saying about the firm through reviews in social media content constitutes a …

Recommender systems are information filtering tools that aspire to predict the rating for
users and items, predominantly from big data to recommend their likes. Movie …

Due to the open and diverse features of the Internet, applications need an effective method
of performing a workflow reconfiguration to achieve both the functional behaviors and non …

Recommender systems are contributing a significant aspect in information filtering and
knowledge management systems. They provide explicit and reliable recommendations to …

Recommender Systems deal with the issue of overloading information by retrieving the most
relevant sources in the wide range of web services. They help users by predicting their …

Failure prediction for hard disk drives is a typical and effective approach to improve the
reliability of storage systems. In a large-scale data center environment, the various brands …

Recommender systems have been regarded as gaining a more significant role with the
emergence of the first research article on collaborative filtering (CF) in the mid-1990s. CF …

Music recommender systems is an important field of research because of easy availability
and use of online music. The most existing models only focus on explicit data like ratings …

Numerous rating prediction approaches have exploited users' review texts to learn the
associated preference knowledge or content semantics in order to make more accurate …