1. bookVolume 21 (2020): Issue 4 (December 2020)
Journal Details
License
Format
Journal
eISSN
1407-6179
First Published
20 Mar 2000
Publication timeframe
4 times per year
Languages
English
Open Access

Exploring an Ensemble of Textual Machine Learning Methodologies for Traffic Event Detection and Classification

Published Online: 26 Nov 2020
Volume & Issue: Volume 21 (2020) - Issue 4 (December 2020)
Page range: 285 - 294
Journal Details
License
Format
Journal
eISSN
1407-6179
First Published
20 Mar 2000
Publication timeframe
4 times per year
Languages
English

1. Abirami, A. and Gayathri, V. (2017) A survey on sentiment analysis methods and approach, in Advanced Computing (ICoAC), 2016 Eighth International Conference on, 2017: IEEE, pp. 72-76.Search in Google Scholar

2. Aiello, L-C., Petkos, G., Martin, C., Corney, D., Papadopoulos, S., Skraba, R., Göker, A. (2013) Sensing trending topics in Twitter, IEEE Transactions in Multimedia, 15(6), pp. 1268–1282.Search in Google Scholar

3. Alhumoud, S. (2019) Twitter Analysis for Intelligent Transportation. The Computer Journal 62, 1547–1556. https://doi.org/10.1093/comjnl/bxy12910.1093/comjnl/bxy129Search in Google Scholar

4. Ali, F., El-Sappagh, S., Kwak, D. (2019) Fuzzy ontology and LSTM-based text mining: A transportation network monitoring system for assisting travel. Sensors, 19(2), 234.10.3390/s19020234635877130634527Search in Google Scholar

5. Alotaibi, S.; Mehmood, R.; Katib, I. (2019) Sentiment Analysis of Arabic Tweets in Smart Cities: A Review of Saudi Dialect. In Proceedings of the 2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC), Rome, Italy, June 10–13, pp. 330–335.10.1109/FMEC.2019.8795331Search in Google Scholar

6. Aqib, M., Mehmood, R., Alzahrani, A., Katib, I., Albeshri, A., Altowaijri, S.M. (2019) Smarter Traffic Prediction Using Big Data, In-Memory Computing, Deep Learning and GPUs. Sensors 19, 2206. https://doi.org/10.3390/s1909220610.3390/s19092206653933831086055Search in Google Scholar

7. Chang, H., Lee, Y., Yoon, B., Baek, S. (2012) Dynamic near-term traffic flow prediction: system-oriented approach based on past experiences. IET Intel. Transport Systems 6, 292–305. doi:10.1049/iet-its.2011.0123.10.1049/iet-its.2011.0123Search in Google Scholar

8. D’Andrea, E., Ducange, P., Lazzerini, B., ---amp--- Marcelloni, F. (2015) Real-time detection of traffic from twitter stream analysis. IEEE transactions on intelligent transportation systems, 16(4), 2269-2283.10.1109/TITS.2015.2404431Search in Google Scholar

9. Dabiri, S., Heaslip, K. (2019) Developing a Twitter-based traffic event detection model using deep learning architectures. Expert systems with applications, Vol. 118, pp. 425-439.10.1016/j.eswa.2018.10.017Search in Google Scholar

10. Ding, J. (2019) Investigation on the Traffic Flow Based on Wireless Sensor Network Technologies Combined with FA-BPNN Models, Journal of Internet Technology, Vol. 20, No. 2, pp. 589-597.Search in Google Scholar

11. Essien, A., Petrounias, I., Sampaio, P., ---amp--- Sampaio, S. (2020) A deep-learning model for urban traffic flow prediction with traffic events mined from twitter. World Wide Web, 1-24. https://doi.org/10.1007/s11280-020-00800-310.1007/s11280-020-00800-3Search in Google Scholar

12. Goswami, A., ---amp--- Kumar, A. (2019) Event Detection Using Twitter Platform. In Digital Business, pp. 429-480. Springer, Cham.10.1007/978-3-319-93940-7_18Search in Google Scholar

13. Gu, Y., Qian, Z. S., ---amp--- Chen, F. (2016) From Twitter to detector: Real-time traffic incident detection using social media data. Transportation research part C: emerging technologies, 67, pp. 321-342. https://doi.org/10.1016/j.trc.2016.02.01110.1016/j.trc.2016.02.011Search in Google Scholar

14. Karita, S., Chen, N., Hayashi, T., Hori, T., Inaguma, H., Jiang, Z., Someki, M., Soplin, N.E.Y., Yamamoto, R., Wang, X. and Watanabe, S. (2019) A comparative study on transformer vs RNN in speech applications. In: 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), pp. 449-456.10.1109/ASRU46091.2019.9003750Search in Google Scholar

15. Khairnar, J., and Kinikar, M. (2013) Machine learning algorithms for opinion mining and sentiment classification, International Journal of Scientific and Research Publications, 3(6), pp. 1-6.Search in Google Scholar

16. Kim, Y., (2014) Convolutional neural networks for sentence classification. arXiv preprint arXiv:1408.5882.10.3115/v1/D14-1181Search in Google Scholar

17. Kokkinos, K., Nathanail, E., ---amp--- Papageorgiou, E. (2018) Applying Unsupervised and Supervised Machine Learning Methodologies in Social Media Textual Traffic Data. In: The 4th Conference on Sustainable Urban Mobility (pp. 665-672). Springer, Cham.10.1007/978-3-030-02305-8_80Search in Google Scholar

18. Lu, Z., Xia, J., Wang, M., Nie, Q., ---amp--- Ou, J. (2020) Short-term traffic flow forecasting via multi-regime modeling and ensemble learning. Applied Sciences, 10(1), 356.10.3390/app10010356Search in Google Scholar

19. Mazoyer, B., Cagé, J., Hervé, N., ---amp--- Hudelot, C. (2020) A french corpus for event detection on twitter. In Proceedings of the 12th Language Resources and Evaluation Conference pp. 6220-6227.Search in Google Scholar

20. Mostafaeipour, A., Rafsanjani, A. J., Ahmadi, M., ---amp--- Dhanraj, J. A. (2020) Investigating the performance of Hadoop and Spark platforms on machine learning algorithms. Journal of SuperComputing.10.1007/s11227-020-03328-5Search in Google Scholar

21. Osman, A. M. S. (2019) A novel big data analytics framework for smart cities. Future Generation Computer Systems, 91, 620-633.10.1016/j.future.2018.06.046Search in Google Scholar

22. Porter, M. F. (1980) An algorithm for suffix stripping, Program: Electron. Library Inf. Syst., 14(3), pp 130–137.Search in Google Scholar

23. Shim, J. P., French, A. M., Guo, C., ---amp--- Jablonski, J. (2015) Big data and analytics: Issues, solutions, and ROI. Communications of the Association for Information Systems, 37(1), 39.10.17705/1CAIS.03739Search in Google Scholar

24. Social Feed Manager, (2020) A social network data acquisition software, https://gwu-libraries.github.io/sfmui/ (last accessed, July 20th, 2020).Search in Google Scholar

25. Suma, S., Mehmood, R., Albugami, N., Katib, I., ---amp--- Albeshri, A. (2017) Enabling next generation logistics and planning for smarter societies. Procedia Computer Science, 109, 1122-1127.10.1016/j.procs.2017.05.440Search in Google Scholar

26. Tanuja, U., Gururaj, H. L., ---amp--- Janhavi, V. (2020) A Machine Learning Algorithm for Classification, Analyzation and Prediction of Multimedia Messages in Social Networks. In Proceedings of First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019) (pp. 485-499). Springer, Singapore.10.1007/978-981-15-3369-3_37Search in Google Scholar

27. Tsai, C. W., Lai, C. F., Chao, H. C., ---amp--- Vasilakos, A. V. (2015) Big data analytics: a survey. Journal of Big data, 2(1), pp. 1-32.10.1186/s40537-015-0030-3Search in Google Scholar

28. Wongcharoen, S., ---amp--- Senivongse, T. (2016) Twitter analysis of road traffic congestion severity estimation. In 13th International Joint Conference on Computer Science and Software Engineering (JCSSE) (pp. 1-6). IEEE.10.1109/JCSSE.2016.7748850Search in Google Scholar

29. Xin, Y., ---amp--- MacEachren, A. M. (2020) Characterizing traveling fans: a workflow for event-oriented travel pattern analysis using Twitter data. International Journal of Geographical Information Science, 1-20.10.1080/13658816.2020.1770259Search in Google Scholar

30. Zhou, Y., and Cao, Z.-W. (2011) Research on the construction and filter method of stop-word list in text preprocessing. In: Proc. 4th ICICTA, Shenzhen, China, vol. 1, pp. 217–221.Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo