A survey on stream-based recommender systems
Recommender Systems (RS) have proven to be effective tools to help users overcome
information overload, and significant advances have been made in the field over the past …
information overload, and significant advances have been made in the field over the past …
Recommender system based on temporal models: a systematic review
Over the years, the recommender systems (RS) have witnessed an increasing growth for its
enormous benefits in supporting users' needs through map** the available products to …
enormous benefits in supporting users' needs through map** the available products to …
Positive, negative and neutral: Modeling implicit feedback in session-based news recommendation
News recommendation for anonymous readers is a useful but challenging task for many
news portals, where interactions between readers and articles are limited within a temporary …
news portals, where interactions between readers and articles are limited within a temporary …
A critical study on data leakage in recommender system offline evaluation
Recommender models are hard to evaluate, particularly under offline setting. In this article,
we provide a comprehensive and critical analysis of the data leakage issue in recommender …
we provide a comprehensive and critical analysis of the data leakage issue in recommender …
A survey on incremental update for neural recommender systems
P Zhang, S Kim - arxiv preprint arxiv:2303.02851, 2023 - arxiv.org
Recommender Systems (RS) aim to provide personalized suggestions of items for users
against consumer over-choice. Although extensive research has been conducted to address …
against consumer over-choice. Although extensive research has been conducted to address …
Applying matrix factorization in collaborative filtering recommender systems
R Barathy, P Chitra - 2020 6th international conference on …, 2020 - ieeexplore.ieee.org
Collaborative filtering plays a vital part in advancing the recommendation environment by
using the matrix factorization (MF) decomposition technology which is demonstrated to be …
using the matrix factorization (MF) decomposition technology which is demonstrated to be …
Using consumer feedback from location-based services in PoI recommender systems for people with autism
Abstract When suggesting Points of Interest (PoIs) to people with autism spectrum disorders,
we must take into account that they have idiosyncratic sensory aversions to noise …
we must take into account that they have idiosyncratic sensory aversions to noise …
Modeling sentimental bias and temporal dynamics for adaptive deep recommendation system
Recommendation systems rely on the historic data of users' purchases and their feedbacks
to profile their preferences and make future recommendations. Most of these systems …
to profile their preferences and make future recommendations. Most of these systems …
Hybrid ecommerce recommendation model incorporating product taxonomy and folksonomy
In modern ecommerce platforms, product content information may have two origins: one is
tree-structured taxonomy attributes, and the other is free-form folksonomy tags. This paper …
tree-structured taxonomy attributes, and the other is free-form folksonomy tags. This paper …
Incorporating a topic model into a hypergraph neural network for searching-scenario oriented recommendations
X Huang, X Liu - Applied Sciences, 2022 - mdpi.com
The personalized recommendation system is a useful tool adopted by e-retailers to help
consumers to find items in line with their preferences. Existing methods focus on learning …
consumers to find items in line with their preferences. Existing methods focus on learning …