With the rapid development of information technology, platform-facilitated collaborative
consumption has recently become attractive to consumers. A comparative study of …

Recommender systems are an integral part of modern-day user experience. They
understand their preferences and support them in discovering meaningful content by …

In recent years, latent semantic analysis (LSA) has reached a level of maturity at which its
presence is ubiquitous in technology as well as in simulation of cognitive processes. In spite …

With the rapid growth of information technology, the amount of unstructured text data in
digital libraries is rapidly increased and has become a big challenge in analyzing …

In the traditional content-based recommendation method, we usually use the movies users
watched before or rated to represent their profile. However, there are many movies that …

Receiving customer opinions on products and services provided by companies is one of the
main needs of company managers to improve products and services. Today, it is common to …

The act of reading has benefits for individuals and societies, yet studies show that reading
declines, especially among the young. Recommender systems can help stop such decline …

Businesses use the platform economy and electronic word-of-mouth generated by online
reviews to attract consumers. Based on the communication accommodation theory, we …

Machine learning-driven recommendation systems are widely used in today's growing
digital world. Existing movie and book recommender systems work using a collaborative …

Over the last decade, quantitative text mining approaches to content analysis have gained
increasing traction within information systems research, and related fields, such as business …