Hybrid scientific article recommendation system with COOT optimization

Sivasankari, R.; Dhilipan, J.

doi:10.1016/j.dsm.2023.11.002

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Other1

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Research on Digital Book Resource Recommendation Algorithm Based on Knowledge Graph

Sun

2024

Procedia Computer Science

View full text Add to dashboard Cite

Research on Digital Book Resource Recommendation Algorithm Based on Knowledge Graph

Sun

2024

Procedia Computer Science

View full text Add to dashboard Cite

Andrioid mobile application aimed at getting personalized recommendations when selecting references

Gerasimova,

Egarmin,

Petrova

et al. 2024

E3S Web of Conf.

View full text Add to dashboard Cite

This article presents the results of the development of a mobile recommendation application to help library readers select references. One of the tasks of a librarian is to provide consultative assistance to the reader in selecting books. Working with a librarian can be replaced by the use of electronic library systems or special programs, which will allow you to solve the same task in less time. At the moment, there are websites and digital libraries that help the user to select books for further reading. They implement various algorithms that allow you to create personalized recommendations. Such systems are designed for electronic reading and are not linked to the databases of municipal library systems. Library readers can obtain recommendations when they choose literature for further reading using a mobile application. The paper considers the process of its creation: analysis of program requirements, design, implementation, testing and implementation. The application is developed for the Android operating system in the integrated development environment Android Studio in the Java programming language. The calculation of the technical and economic indicators of the project in its implementation has shown that the use of the application will provide sufficient economic effect. Its use can simplify the process of selecting books and significantly reduce the time to search for them, thus giving the librarian the opportunity to perform other tasks. The program does not require material costs for installation, which is an obvious advantage, and the functionality and system requirements allow its use on all mobile devices with the Android operating system.

show abstract

Machine Learning Based Item Recommendation System for Surplus Item Sharing System

Terence,

Immaculate,

Kranthi

et al. 2024

2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC)

View full text Add to dashboard Cite

Hybrid scientific article recommendation system with COOT optimization

Cited by 3 publications

References 13 publications

Research on Digital Book Resource Recommendation Algorithm Based on Knowledge Graph

Research on Digital Book Resource Recommendation Algorithm Based on Knowledge Graph

Andrioid mobile application aimed at getting personalized recommendations when selecting references

Machine Learning Based Item Recommendation System for Surplus Item Sharing System

Contact Info

Product

Resources

About