Artificial intelligence in E-Commerce: a bibliometric study and literature review
This paper synthesises research on artificial intelligence (AI) in e-commerce and proposes
guidelines on how information systems (IS) research could contribute to this research …
guidelines on how information systems (IS) research could contribute to this research …
Application of Internet of Things and artificial intelligence for smart fitness: A survey
A Farrokhi, R Farahbakhsh, J Rezazadeh, R Minerva - Computer Networks, 2021 - Elsevier
The revolution of Internet of Things (IoT) is pervading many facets of our everyday life.
Among the multiple IoT application domains, well-being is becoming one of the popular …
Among the multiple IoT application domains, well-being is becoming one of the popular …
Recommendation systems: Algorithms, challenges, metrics, and business opportunities
Recommender systems are widely used to provide users with recommendations based on
their preferences. With the ever-growing volume of information online, recommender …
their preferences. With the ever-growing volume of information online, recommender …
Recommender systems for smart cities
Among other conceptualizations, smart cities have been defined as functional urban areas
articulated by the use of Information and Communication Technologies (ICT) and modern …
articulated by the use of Information and Communication Technologies (ICT) and modern …
A systematic study on the recommender systems in the E-commerce
Electronic commerce or e-commerce includes the service and good exchange through
electronic support like the Internet. It plays a crucial role in today's business and users' …
electronic support like the Internet. It plays a crucial role in today's business and users' …
Content-based filtering for recommendation systems using multiattribute networks
J Son, SB Kim - Expert Systems with Applications, 2017 - Elsevier
Abstract Content-based filtering (CBF), one of the most successful recommendation
techniques, is based on correlations between contents. CBF uses item information …
techniques, is based on correlations between contents. CBF uses item information …
A recommendation engine for predicting movie ratings using a big data approach
In this era of big data, the amount of video content has dramatically increased with an
exponential broadening of video streaming services. Hence, it has become very strenuous …
exponential broadening of video streaming services. Hence, it has become very strenuous …
Hierarchical user profiling for e-commerce recommender systems
Hierarchical user profiling that aims to model users' real-time interests in different granularity
is an essential issue for personalized recommendations in E-commerce. On one hand, items …
is an essential issue for personalized recommendations in E-commerce. On one hand, items …
Mining user interest based on personality-aware hybrid filtering in social networks
With the emergence of online social networks and microblogging websites, user interest
mining has been an active research topic for the past few years. However, most of the …
mining has been an active research topic for the past few years. However, most of the …
User profile correlation-based similarity (UPCSim) algorithm in movie recommendation system
Collaborative filtering is one of the most widely used recommendation system approaches.
One issue in collaborative filtering is how to use a similarity algorithm to increase the …
One issue in collaborative filtering is how to use a similarity algorithm to increase the …