Artificial intelligence (AI) for user experience (UX) design: a systematic literature review and future research agenda
Purpose The aim of this article is to map the use of AI in the user experience (UX) design
process. Disrupting the UX process by introducing novel digital tools such as artificial …
process. Disrupting the UX process by introducing novel digital tools such as artificial …
Advancements and challenges in machine learning: A comprehensive review of models, libraries, applications, and algorithms
In the current world of the Internet of Things, cyberspace, mobile devices, businesses, social
media platforms, healthcare systems, etc., there is a lot of data online today. Machine …
media platforms, healthcare systems, etc., there is a lot of data online today. Machine …
Enhancing brick-and-mortar store shop** experience with an augmented reality shop** assistant application using personalized recommendations and …
Purpose The transition to omnichannel retail is the recognized future of retail, which uses
digital technologies (eg augmented reality shop** assistants) to enhance the customer …
digital technologies (eg augmented reality shop** assistants) to enhance the customer …
Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and application
Blockchain technology (BT) allows market participants to keep track of digital transactions
without central recordkee**. The features of blockchain, including decentralization …
without central recordkee**. The features of blockchain, including decentralization …
HetNERec: Heterogeneous network embedding based recommendation
Traditional recommendation techniques are hindered by the simplicity and sparsity of user-
item interaction data and can be improved by introducing auxiliary information related to …
item interaction data and can be improved by introducing auxiliary information related to …
[HTML][HTML] Comparison of decision tree based ensemble methods for prediction of photovoltaic maximum current
The intermittent nature of the output power of photovoltaic (PV) systems, in addition to the
fast-varying solar irradiance, has prompted the development of fast, accurate, and reliable …
fast-varying solar irradiance, has prompted the development of fast, accurate, and reliable …
A real-life machine learning experience for predicting university dropout at different stages using academic data
High levels of school dropout are a major burden on the educational and professional
development of a country's inhabitants. A country's prosperity depends, among other factors …
development of a country's inhabitants. A country's prosperity depends, among other factors …
Creating a recommender system to support higher education students in the subject enrollment decision
Higher Education plays a principal role in the changing and complex world of today, and
there has been rapid growth in the scientific literature dedicated to predicting students' …
there has been rapid growth in the scientific literature dedicated to predicting students' …
[PDF][PDF] A survey of big data and machine learning.
SR Salkuti - … Journal of Electrical & Computer Engineering …, 2020 - pdfs.semanticscholar.org
This paper presents a detailed analysis of big data and machine learning (ML) in the
electrical power and energy sector. Big data analytics for smart energy operations …
electrical power and energy sector. Big data analytics for smart energy operations …
Attentive meta-graph embedding for item recommendation in heterogeneous information networks
Heterogeneous information network (HIN) has become increasingly popular to be exploited
in recommender systems, since it contains abundant semantic information to help generate …
in recommender systems, since it contains abundant semantic information to help generate …