Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Hybridoma Technology01:31

Hybridoma Technology

14.1K
Hybridoma technology is used for the large-scale production of monoclonal antibodies. Monoclonal antibodies bind to only a single antigenic determinant or epitope. Such antibodies are used in research, diagnostics, and disease therapy. The hybridoma technology established in 1975 by Georges Köhler and Cesar Milstein was awarded the Nobel Prize in Medicine in 1984 for revolutionizing research and therapy.
Hybridoma Selection
Commonly used fusion techniques — electroporation,...
14.1K
Hybrid Zones02:29

Hybrid Zones

16.8K
Hybrid zones are narrow regions where two closely related species interact, mate, and produce hybrids. Relative to either parent species, hybrids may possess distinct phenotypic or genetic differences that impact their survival and reproductive success. The genetic variances introduced by hybridization influence species diversity and speciation processes within the hybrid zone.
16.8K
Reliability and Validity01:29

Reliability and Validity

12.7K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
12.7K
Systematic Sampling Method01:17

Systematic Sampling Method

10.0K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
10.0K
Stereotype Content Model02:16

Stereotype Content Model

14.0K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.0K
Group Design02:01

Group Design

8.9K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
8.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Prevalence, Risk Factors, Disease-Related Knowledge, and Vaccination Attitudes and Behaviors for Long COVID Among French Civil Servants: Cross-Sectional Survey.

JMIR public health and surveillance·2025
Same author

Impact of Face Mask-Wearing on Quality of Life in Post-Surgical Oral Cancer Patients: A Cross-Sectional Study.

Cancers·2025
Same author

Multimodal Machine Learning for Predicting Post-Surgery Quality of Life in Colorectal Cancer Patients.

Journal of imaging·2024
Same author

French Version of the User Mobile Application Rating Scale: Adaptation and Validation Study.

JMIR mHealth and uHealth·2024
Same author

Investigating Contrastive Pair Learning's Frontiers in Supervised, Semisupervised, and Self-Supervised Learning.

Journal of imaging·2024

Related Experiment Video

Updated: May 31, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K

Hybrid Quality-Based Recommender Systems: A Systematic Literature Review.

Bihi Sabiri1, Amal Khtira2, Bouchra El Asri1

  • 1IMS Team, ADMIR Laboratory, Rabat IT Center, ENSIAS, Mohammed V University in Rabat, Rabat 10130, Morocco.

Journal of Imaging
|January 24, 2025
PubMed
Summary
This summary is machine-generated.

Hybrid recommender systems enhance e-commerce by improving product visibility and user experience. This systematic review examines recent advancements, challenges, and opportunities in hybrid recommendation approaches.

Keywords:
big datahybrid quality-based recommendationsstrategy recommender systemssystematic review

More Related Videos

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

9.5K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

484

Related Experiment Videos

Last Updated: May 31, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K
Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

9.5K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

484

Area of Science:

  • Computer Science
  • Information Science
  • E-commerce Technology

Background:

  • Consumer behavior and search patterns are evolving with technology, impacting e-commerce.
  • Recommender systems are crucial for increasing product visibility and sales in online retail.
  • Hybrid recommender systems, combining multiple methodologies, are a significant research focus.

Purpose of the Study:

  • To conduct a systematic review of recent developments in hybrid recommender systems.
  • To assess progress, identify common approaches, explore technical contexts, and highlight research gaps.
  • To provide insights into the design and implementation of hybrid recommender systems, considering big data challenges.

Main Methods:

  • Systematic literature review adhering to Cochrane Handbook and Kitchenham & Charters principles.
  • Searched ACM, Google Scholar, Scopus, Springer (last 4 years) and Web of Science (all years).
  • Utilized ASReview, an open-source active learning application for efficient literature filtering.

Main Results:

  • Analysis of hybrid recommender system trends, practical applications, strengths, and limitations.
  • Identification of key challenges and opportunities in big data (volume, velocity, variety) for hybrid systems.
  • Overview of the current state-of-the-art in hybrid recommendation algorithms.

Conclusions:

  • Hybrid recommender systems are vital for modern e-commerce, offering enhanced user experiences and sales.
  • Further research is needed to address big data challenges and refine hybrid approaches.
  • This review provides a foundation for future research in optimizing hybrid recommender systems.