Open Access
| Issue |
EPJ Web Conf.
Volume 367, 2026
Fifth International Conference on Robotics, Intelligent Automation and Control Technologies (RIACT 2026)
|
|
|---|---|---|
| Article Number | 02008 | |
| Number of page(s) | 29 | |
| Section | Intelligent Automation | |
| DOI | https://doi.org/10.1051/epjconf/202636702008 | |
| Published online | 29 April 2026 | |
- M. Danandeh Oskouei and S. N. Razavi, A survey of web spam detection techniques, Int. J. Comput. Appl. Technol. Res. 3, 180–185 (2014). [Google Scholar]
- K. L. Goh, A. Singh, R. Kumar and A. Mohan, TPRank: Contend with web spam using trust propagation, Cybern. Syst. 45 (2014). [Google Scholar]
- K. L. Goh, R. K. Patchmuthu and A. K. Singh, Link-based web spam detection using weight properties, J. Intell. Inf. Syst. 43, 129–145 (2014). [Google Scholar]
- K. L. Goh, R. K. Patchmuthu and A. K. Singh, Distrust seed set propagation algorithm to detect web spam, J. Intell. Inf. Syst. 49, 213–235 (2017). [Google Scholar]
- Y. Guo, X. J. Yang and C. Shi, TIP: A trust inference and propagation model in multi- human multi-robot teams, Auton. Robots 48 (2024). [Google Scholar]
- J. Baladasan and K. Desikan, Weighted PageRank algorithm based on in-out weight of webpages, Indian J. Sci. Technol. 8 (2015). [Google Scholar]
- E. Khalastchi, Fault detection and diagnosis in multi-robot systems: A survey, Sensors 19, 4019 (2019). [Google Scholar]
- X. Liu, Y. Wang, S. Zhu and H. Lin, Combating web spam through trust–distrust prop- agation with confidence, Pattern Recognit. Lett. 34, 1462–1469 (2013). [Google Scholar]
- A. Makkar and N. Kumar, An efficient deep learning-based scheme for web spam de- tection in IoT environment, Future Gener. Comput. Syst. 108, 467–487 (2020). [Google Scholar]
- V. Quang, H. Viet, V. Long and T. Khang, An Improved AdaBoost Algorithm for Highly Imbalanced Datasets in the Co-Authorship Recommendation Problem, IEEE Access PP (2023), pp. 1–1. [Google Scholar]
- A. K. Srivastava, R. Garg and P. K. Mishra, Discussion on damping factor value in PageRank computation, Int. J. Intell. Syst. Appl. 9, 19–28 (2017). [Google Scholar]
- J. Whang, Y. Jung, I. S. Dhillon, S. Kang and J. Lee, Fast asynchronous Anti-TrustRank for web spam detection, (2018). [Google Scholar]
- B. Wu, V. Goel and B. D. Davison, Propagating trust and distrust to demote web spam, In: Workshop on Models of Trust for the Web, (2006). [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.