Introduction on health recommender systems.
Explore this paper's citation graph
Summary
The main goals of health recommender systems are to retrieve trusted health information from the Internet, to analyse which is suitable for the user profile and select the best that can be recommended, to adapt their selection methods according to the knowledge domain and to learn from the best recommendations.
- Type
- article
- Published
- 2015-01-01
- Cited by
- 17
- References
- 30
- OpenAlex
- https://openalex.org/W2416373596
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:38035079
Keywords
Recommender system, Computer science, World Wide Web
References
- Personal health records.
- Hybrid Recommender Systems: Survey and Experiments
- Integrating Association Rule Mining with Relational Database Systems: Alternatives and Implications
- Industry Report: Amazon.com Recommendations: Item-to-Item Collaborative Filtering
- Recommender Systems: Introduction
- Binding ontologies and coding systems to electronic health records and messages
- Application of Dimensionality Reduction in Recommender System - A Case Study
- Mobile Recommender Systems
- Associative semantic network dysfunction in thought-disordered schizophrenic patients: direct evidence from indirect semantic priming.
- Increasing patient safety using explanation-driven personalized content recommendation
- HealthTrust: A Social Network Approach for Retrieving Online Health Videos
- Algorithms for association rule mining — a general survey and comparison
- Consumer health information seeking on the Internet: the state of the art.
- Matrix Factorization Techniques for Recommender Systems
- Adapting recommender systems to the requirements of personal health record systems
- Improving the retrieval of information from external sources
- Training algorithms for linear text classifiers
- Opinion Mining and Sentiment Analysis
- Jena: implementing the semantic web recommendations
- Building a Transnational Biosurveillance Network Using Semantic Web Technologies: Requirements, Design, and Preliminary Evaluation
Cited by
- Why do people (not) like me?: Mining opinion influencing factors from reviews
- HealthRecSys: A semantic content-based recommender system to complement health videos
- Healthrecsys: Sistema recomendador para la salud
- Towards a Knowledge-Based Recommender System for Linking Electronic Patient Records With Continuing Medical Education Information at the Point of Care
- Recomendação de recursos de infraestrutura necessários para a implementação de processos a partir de rótulos de modelos de processo.
- Improving information retrieval from electronic health records using dynamic and multi-collaborative filtering
- Recommender systems in the healthcare domain: state-of-the-art and research issues
- RecoMed: A Knowledge-Aware Recommender System for Hypertension Medications
- A personalized agent-based chatbot for nutritional coaching
- Ethical and legal considerations for nutrition virtual coaches
- Development and Evaluation of Health Recommender Systems: Systematic Scoping Review and Evidence Mapping
- Rethinking Health Recommender Systems for Active Aging: An Autonomy-Based Ethical Analysis
- A knowledge graph-based recommender system for dementia care: Design and evaluation study
- Dissemination and implementation research in health recommender systems: a systematic scoping review and evidence map (Preprint)
- Content‐Based Health Recommender Systems
- Review of Machine Learning and Deep Learning Based Recommender Systems for Health Informatics
- Mapping Digital Nudges and Recommender Systems for Obesity Prevention: Scoping Review
Related papers
- ИСПОЛЬЗОВAНИЕ ПОТЕНЦИAЛA СОЦИAЛЬНЫХ ПAРТНЕРОВ В ПОДГОТОВКЕ БУДУЩИХ ПЕДAГОГОВ
- Recommender systems: models, challenges and opportunities
- Hybrid-based Research Article Recommender System
- Design and evaluation of a recommender system
- A Hypothesis is Placed to Justify the Extendibility of Recommender System/ Recommendation System into Social Life
- An Overview of the Recommender System
- A Hypothesis is Placed to Justify the Extendibility of Recommender System/ Recommendation System into Social Life