The use of machine learning algorithms in recommender systems: A systematic review
I Portugal, P Alencar, D Cowan - Expert Systems with Applications, 2018 - Elsevier
Recommender systems use algorithms to provide users with product or service
recommendations. Recently, these systems have been using machine learning algorithms …
recommendations. Recently, these systems have been using machine learning algorithms …
A comprehensive survey on local differential privacy toward data statistics and analysis
T Wang, X Zhang, J Feng, X Yang - Sensors, 2020 - mdpi.com
Collecting and analyzing massive data generated from smart devices have become
increasingly pervasive in crowdsensing, which are the building blocks for data-driven …
increasingly pervasive in crowdsensing, which are the building blocks for data-driven …
Personalized digital marketing recommender engine
E-business leverages digital channels to scale its functions and services and operates by
connecting and retaining customers using marketing initiatives. To increase the likelihood of …
connecting and retaining customers using marketing initiatives. To increase the likelihood of …
[HTML][HTML] An effective collaborative movie recommender system with cuckoo search
Recommender systems are information filtering tools that aspire to predict the rating for
users and items, predominantly from big data to recommend their likes. Movie …
users and items, predominantly from big data to recommend their likes. Movie …
The online dating effect: Where a couple meets predicts the quality of their marriage
LL Sharabi, E Dorrance-Hall - Computers in Human Behavior, 2024 - Elsevier
Drawing on social ecology theory, this study compares the marriages of people who met in
online dating to those who were introduced offline. A survey was administered to a sample …
online dating to those who were introduced offline. A survey was administered to a sample …
New perspectives on gray sheep behavior in E-commerce recommendations
With the exponential rise in the size of data being generated, personalization based on
recommender systems has become an important aspect of digital marketing strategy of E …
recommender systems has become an important aspect of digital marketing strategy of E …
[PDF][PDF] Finding love on a first data: Matching algorithms in online dating
LL Sharabi - Harvard Data Science Review, 2022 - assets.pubpub.org
Column Editor's Note: Dating apps and online matchmaking are now a commonplace way
for couples to meet and relationships to form. As human communications expert Liesel …
for couples to meet and relationships to form. As human communications expert Liesel …
Love on the Spectrum: Toward Inclusive Online Dating Experience of Autistic Individuals
Online dating is a space where autistic individuals can find romantic partners with reduced
social demands. Autistic individuals are often expected to adapt their behaviors to the social …
social demands. Autistic individuals are often expected to adapt their behaviors to the social …
A social recommender system using item asymmetric correlation
Recommender systems have been one of the most prominent information filtering
techniques during the past decade. However, they suffer from two major problems, which …
techniques during the past decade. However, they suffer from two major problems, which …
Optimally balancing receiver and recommended users' importance in reciprocal recommender systems
Online platforms which assist people in finding a suitable partner or match, such as online
dating and job recruiting environments, have become increasingly popular in the last …
dating and job recruiting environments, have become increasingly popular in the last …