Recommender Systems are designed to analysis the available data in the system to predict
user's desires and provide appropriate personalized suggestions to each user that suits their …

Recently, there has been growing interest in recommender systems (RS) and particularly in
context-aware RS. Methods for generating context-aware recommendations are classified …

Now-a-days people are consuming content in form of movies, series, etc. for entertainment.
In this modern era, people always look up to entertainment and in that process, they waste …

To solve the problem that users' retrieval intentions are seldom considered by personalized
websites, we propose an improved incremental collaborative filtering (CF)-based …

Collaborative filtering with a traditional rating-based approach uses interaction records
between users and systems to measure similarity, prediction, and generate …

This paper highlights the current literatures in usability studies, performance metrics and
machine learning algorithm. A literature review is done in these three areas of studies to find …

As a result of rapid advances in information technology, the volume of information on the
Internet is expanding at a breakneck rate. The World Wide Web has evolved into a vast and …

After several decades since its introduction, the existing ISO9241-11 usability framework is
still vastly used in Mobile Augmented Reality (MAR) language learning. The existing …

This paper proposes a methodology that utilizes unsupervised machine learning clustering
techniques in performance based usability data. This paper will first discuss the introduction …

This article presents the experimental work of comparing the performances of two machine
learning approaches, namely Hierarchical Agglomerative Clustering and K-means …