Other useful links, reviews, citations

Feel free to send us a link to your project or research paper related to JATE (either 1.x or 2.x) that you think will be useful or interesting for the others.

Zhang, Z., Gao, J., & Ciravegna, F. (2018). SemRe-Rank: Incorporating Semantic Relatedness to Improve Automatic Term Extraction Using Personalized PageRank. ACM Transactions on Knowledge Discovery from Data (TKDD). Access via https://arxiv.org/abs/1711.03373

Yuan, Y., Gao, J., & Zhang, Y. (2017, October). Supervised Learning for Robust Term Extraction. In The proceedings of 2017 International Conference on Asian Language Processing (IALP). IEEE.

Costa, H., Zaretskaya, A., Pastor, G. C., & Seghiri, M. (2016). Nine terminology extraction tools–Are they useful for translators?. Multilingual, April/May.

Astrakhantsev, N. (2016). ATR4S: Toolkit with State-of-the-art Automatic Terms Recognition Methods in Scala. arXiv preprint arXiv:1611.07804.

Arora, C., Sabetzadeh, M., Briand, L., & Zimmer, F. (2016). Automated Extraction and Clustering of Requirements Glossary Terms. IEEE Transactions on Software Engineering.

Escartin, C. P., Torres, L. S., UoW, C. O., UMA, A. Z., & Pal, S. (2016). D6. 5: Final User Evaluation. Avail: http://expert-itn.eu/sites/default/files/outputs/expert_d6.5_20160830_final_user_evaluation.pdf (accessed on July, 2017)

Chen, J., Jagannatha, A. N., Jarad, S. J., & Yu, H. (2016). Ranking medical jargon in electronic health record notes by adapted distant supervision. arXiv preprint arXiv:1611.04491.

Marín, M. J. (2015) Measuring precision in legal term mining: a corpus-based validation of single and multi-word term recognition methods. English for Special Purposes World, ISSN 1682-3257, www.esp-world.info, Issue 46. Avail: https://www.academia.edu/14515879/Measuring_precision_in_legal_term_mining_a_corpus-based_validation_of_single_and_multi-word_term_recognition_methods (accessed on July, 2017)

Nguyen, M., Ho, T., & Do, P. (2013, November). Social networks analysis based on topic modeling. In Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), 2013 IEEE RIVF International Conference on (pp. 119-122). IEEE.

Arora, C., Sabetzadeh, M., Briand, L., & Zimmer, F. (2014, September). Improving requirements glossary construction via clustering: approach and industrial case studies. In Proceedings of the 8th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (p. 18). ACM.

Temnikova, I. P., Varga, A., & Biyikli, D. (2014). Building a Crisis Management Term Resource for Social Media: The Case of Floods and Protests. In LREC (pp. 740-747).

Lucanský, M., & Simko, M. (2013, January). Improving Relevance of Keyword Extraction from the Web Utilizing Visual Style Information. In SOFSEM (pp. 445-456).

Maldonado, A., & Lewis, D. Self-tuning ongoing terminology extraction retrained on terminology validation decisions. TERM BASES AND LINGUISTIC LINKED OPEN DATA, 91.