Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Combination Therapies and Personalized Medicine

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...

Systematic Sampling Method

Systematic Sampling Method

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...

Combined Effects of Drugs: Synergism

Combined Effects of Drugs: Synergism

Synergism is a useful mechanism where combining two or more drugs is more effective than each constituent used alone. Such combinations are also called supra-additive interactions. The drugs collectively enhance the final therapeutic effect by acting on different targets. Another advantage is that the low dose of each constituent drug is sufficient to achieve the desired effect. This helps reduce the duration of therapy and lower the adverse effects of these drugs.
Such synergistic combinations...

Social Exchange Theory

Social Exchange Theory

We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).

Social Proof

Social proof is a form of persuasion based on comparison and conformity. People compare their behavior and actions to what others are doing and will change to conform to do what their peers do.

Predicting Reaction Outcomes

Predicting Reaction Outcomes

Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...

You might also read

Related Articles

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

Sort by

Same author

Sex-based cardiovascular risk in depressive symptoms.

General hospital psychiatry·2025

Same author

Development of an epilepsy self-management mobile health app framework: Content validity study results.

PloS one·2024

Same author

What is needed to build a personalized recommender system for K-12 students' E-Learning? Recommendations for future systems and a conceptual framework.

Education and information technologies·2022

Same author

Investigating transportation research based on social media analysis: a systematic mapping review.

Scientometrics·2021

Same author

Self-Management Apps for People With Epilepsy: Systematic Analysis.

JMIR mHealth and uHealth·2021

Same author

Correction: A novel association rule mining approach using TID intermediate itemset.

PloS one·2018

Search research articles

Related Experiment Video

Updated: Feb 21, 2026

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

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

Published on: December 11, 2016

A collaborative approach for research paper recommender system.

Khalid Haruna^1,2, Maizatul Akmar Ismail², Damiasih Damiasih³

¹Department of Computer Science, Faculty of Computer Science and Information Technology, Bayero University, Kano, Nigeria.

|October 6, 2017

Summary

This summary is machine-generated.

This study introduces a novel collaborative filtering approach for research paper recommenders. It personalizes recommendations using metadata, overcoming content accessibility issues and improving relevance for all users.

More Related Videos

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

Related Experiment Videos

Last Updated: Feb 21, 2026

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

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

Published on: December 11, 2016

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

Area of Science:

Computer Science
Information Retrieval
Bibliometrics

Background:

Research paper recommender systems aim to connect researchers with relevant publications.
Existing systems often require full content access, which is limited by copyright.
Personalization challenges include varying research fields and user expertise levels.

Purpose of the Study:

To develop a collaborative filtering approach for research paper recommendation.
To overcome limitations of content accessibility in recommender systems.
To provide personalized recommendations irrespective of research field or user expertise.

Main Methods:

Utilized a collaborative filtering approach leveraging publicly available contextual metadata.
Inferred hidden associations between research papers to enable personalized recommendations.
Evaluated the approach using a publicly available dataset against baseline methods.

Main Results:

The proposed approach demonstrated significant improvement in overall performance.
Achieved better results in returning relevant and useful publications at the top of the recommendation list.
Effectively provided personalized recommendations regardless of research field or user expertise.

Conclusions:

The collaborative metadata-based approach enhances research paper recommendation systems.
This method successfully addresses content accessibility limitations.
It offers a robust solution for personalized academic paper discovery.