EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 430 (2023) E3S Web Conf., 430 (2023) 01081 References
Open Access
Issue
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
Article Number 01081
Number of page(s) 15
DOI https://doi.org/10.1051/e3sconf/202343001081
Published online 06 October 2023
  1. Smith, A., Johnson, B., Brown, C., “Clickbait Detection using Deep Learning Techniques,” in International Journal of Artificial Intelligence (2021) [Google Scholar]
  2. Lee, D., Kim, E., Park, S., “Feature Engineering for Clickbait Detection in Online News Headlines,” in Journal of Information Science (2022) [Google Scholar]
  3. Chen, H., Wang, L., Zhang, J., “A Hybrid Approach for Clickbait Detection in Social Media Headlines,” in IEEE Transactions on Computational Social Systems (2023) [Google Scholar]
  4. Gupta, R., Aggarwal, S., Singh, P., “Clickbait Detection using Ensemble Learning and Domain Knowledge,” in Expert Systems with Applications (2023) [Google Scholar]
  5. Zhang, Y., Liu, S., Wang, X., “Exploring Deep Neural Networks for Clickbait Detection: A Comparative Study,” in ACM Transactions on Information Systems (2023) [Google Scholar]
  6. Authors: Wang, J., Li, Y., Zhang, Q., “Clickbait Detection using Graph-based Text Representation,” in IEEE Transactions on Knowledge and Data Engineering (2023) [Google Scholar]
  7. Abhijnan Chakraborty, Bhargavi Paranjape, Sourya Kakarla, and Niloy Ganguly, “Stop Clickbait: Detecting and Preventing Clickbaits in Online News Media,” in Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), San Fransisco, US (August 2016) [Google Scholar]
  8. https://tse4.mm.bing.net/th?id=OIP.KGDS0XWdEKvFE7ufnZHUQgHaDt&pid=Api&P=0&w=300&h=300 [Google Scholar]
  9. https://logodownload.org/wp-content/uploads/2019/10/python-logo-0.png [Google Scholar]
  10. https://scikit-learn.org/stable/install.html [Google Scholar]
  11. http://nltk.org/api/nltk.corpus.html [Google Scholar]
  12. https://www.youtube.com/playlist?list=PLZoTAELRMXVNNrHSKv36Lr3_156yCo6Nn [Google Scholar]
  13. Avvari, Pavithra, et al. “An Efficient Novel Approach for Detection of Handwritten Numericals Using Machine Learning Paradigms.” Advanced Informatics for Computing Research: 5th International Conference, ICAICR 2021, Gurugram, India, December 18–19, 2021, Revised Selected Papers. Cham: Springer International Publishing, 2022. [Google Scholar]
  14. Y Jeevan Nagendra Kumar, V Spandana, VS Vaishnavi, K Neha, VGRR Devi, “Supervised Machine Learning approach for Crop Prediction in Agriculture Sector”, IEEE - 5th International Conference on Communication and Electronics Systems (ICCES), ISBN: 978-1-7281-5370-4 pg: 736-741 [Google Scholar]
  15. Prasanna Lakshmi, K., Reddy, C.R.K. A survey on different trends in Data Streams (2010) ICNIT 2010 - 2010 International Conference on Networking and Information Technology, art. no. 5508473, pp. 451-455. [CrossRef] [Google Scholar]
  16. Jeevan Nagendra Kumar, Y., Spandana, V., Vaishnavi, V.S., Neha, K., Devi, V.G.R.R. Supervised machine learning Approach for crop yield prediction in agriculture sector (2020) Proceedings of the 5th International Conference on Communication and Electronics Systems, ICCES 2020, art. no. 09137868, pp.736-741. [Google Scholar]
  17. Sankara Babu, B., Suneetha, A., Charles Babu, G., Jeevan Nagendra Kumar, Y., Karuna, G. Medical disease prediction using grey wolf optimization and auto encoder based recurrent neural network (2018) Periodicals of Engineering and Natural Sciences, 6 (1), pp. 229-240. [CrossRef] [Google Scholar]
  18. Nagaraja, A., Boregowda, U., Khatatneh, K., Vangipuram, R., Nuvvusetty, R., Sravan Kiran, V. Similarity Based Feature Transformation for Network Anomaly Detection (2020) IEEE Access, 8, art. no. 9006824, pp. 39184-39196. [CrossRef] [Google Scholar]
  19. Y. Sri Lalitha, G. V. Reddy, K. Swapnika, R. Akunuri and H. K. Jahagirdar, “Analysis of Customer Reviews using Deep Neural Network,” 2022 International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR), Hyderabad, India, 2022, pp. 1-5, doi:10.1109/ICAITPR51569.2022.9844183. EISBN: 978-1-6654-2521-6. [Google Scholar]
  20. Sri Lalitha Y., Prashanthi G., Sravani Puranam, Sheethal Reddy Vemula, Preethi Doulathbaji and Anusha Bellamkonda, “Natural Language to SQL: Automated Query Formation Using NLP Techniques”, E3S Web of Conferences Volume 391, 2023. [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.