Article detail · 2021
Big Data Testing Framework for Recommendation Systems in e-Science and e-Commerce Domains
Journal
2021 IEEE International Conference on Big Data (Big Data)- Year
- 2021
- Type
- conference-paper
Data source split
- YÖKSİS venue 2021 IEEE International Conference on Big Data (Big Data)
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
Software testing is an important process to evaluate whether the developed software applications meet the required specifications. There is an emerging need for testing frameworks for big data software projects to ensure the quality of the big data applications and satisfy the user requirements. In this study, we propose a software testing framework that can be utilized in big data projects both in e-science and e-commerce. In particular, we design the proposed framework to test big data-based recommendation applications. To show the usability of the proposed framework, we provide a reference prototype implementation and use the prototype to test a big data recommendation application. We apply the prototype implementation to test both functional and non-functional methods of the recommendation application. The results indicate that the proposed testing framework is usable and efficient for testing the recommendation systems that use big data processing techniques.
Topics
Citations
OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.
21 citations
OpenAlex cited_by_count (cache / database)
5 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
- On the big data processing algorithms for finding frequent sequences 2025
- A Novel Sequential Pattern Mining Algorithm for Large Scale Data Sequences 2022
- A Novel Approach to Recommendation System Business Workflows: A Case Study for Book E-Commerce Websites 2022
- Kullanıcı ve Öğe Bazlı, Geniş ve Derin Öğrenme Tabanlı Seyahat Öneri Sistemi 2023
- Methodology for Product Recommendation Based on User-System Interaction Data: A Case Study on Computer Systems E-Commerce Web Site 2022