A review of movie recommendation system: Limitations, Survey and Challenges
M Goyani, N Chaurasiya - ELCVIA: electronic letters on computer vision …, 2020 - ddd.uab.cat
Recommendation System is a major area which is very popular and useful for people to take
proper decision. It is a method that helps user to find out the information which is beneficial …
proper decision. It is a method that helps user to find out the information which is beneficial …
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 …
Design and analysis of a cluster-based intelligent hybrid recommendation system for e-learning applications
S Bhaskaran, R Marappan, B Santhi - Mathematics, 2021 - mdpi.com
Recently, different recommendation techniques in e-learning have been designed that are
helpful to both the learners and the educators in a wide variety of e-learning systems …
helpful to both the learners and the educators in a wide variety of e-learning systems …
Movie popularity and target audience prediction using the content-based recommender system
The movie is one of the integral components of our everyday entertainment. The worldwide
movie industry is one of the most growing and significant industries and seizing the attention …
movie industry is one of the most growing and significant industries and seizing the attention …
A hybrid recommendation system of upcoming movies using sentiment analysis of youtube trailer reviews
Movies are one of the integral components of our everyday entertainment. In today's world,
people prefer to watch movies on their personal devices. Many movies are available on all …
people prefer to watch movies on their personal devices. Many movies are available on all …
Design and comparative analysis of new personalized recommender algorithms with specific features for large scale datasets
S Bhaskaran, R Marappan, B Santhi - Mathematics, 2020 - mdpi.com
Nowadays, because of the tremendous amount of information that humans and machines
produce every day, it has become increasingly hard to choose the more relevant content …
produce every day, it has become increasingly hard to choose the more relevant content …
[HTML][HTML] Zero-Shot Content-Based Crossmodal Recommendation System
Abstract Information Recommendation (IR) systems are conventionally designed to operate
within a single modality at a time, such as Text2Text or Image2Image. However, the concept …
within a single modality at a time, such as Text2Text or Image2Image. However, the concept …
User behavior modeling for AR personalized recommendations in spatial transitions
There have been studies on personalized augmented reality (AR) systems taking users'
contexts and histories into account. However, there is insufficient research on incorporating …
contexts and histories into account. However, there is insufficient research on incorporating …
Recommendation System for a Delivery Food Application Based on Number of Orders
CN Sánchez, J Domínguez-Soberanes, A Arreola… - Applied Sciences, 2023 - mdpi.com
With the recent growth in food-delivery applications, creating new recommendation systems
tailored to this platform is essential. State-of-the-art restaurant recommendation systems are …
tailored to this platform is essential. State-of-the-art restaurant recommendation systems are …
Behavior driven development: Tools and challenges
RK Lenka, S Kumar, S Mamgain - … International Conference on …, 2018 - ieeexplore.ieee.org
Nowadays testing usually applies Test Driven Development (TDD) which is an approach to
software development in which developers write tests first which initially fail and by adding …
software development in which developers write tests first which initially fail and by adding …