{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T17:33:12Z","timestamp":1763573592669,"version":"3.45.0"},"publisher-location":"Gdansk, Poland; Belgrade, Serbia","reference-count":30,"publisher":"University of Gdansk, Department of Business Informatics & University of Belgrade, Faculty of Organizational Sciences","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.62036\/isd.2025.3","type":"proceedings-article","created":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T00:45:28Z","timestamp":1763513128000},"source":"Crossref","is-referenced-by-count":0,"title":["Automation of Selected Processes in IT Project Management with Natural Language Processing"],"prefix":"10.62036","author":[{"given":"Aneta","family":"Poniszewska-Maranda","sequence":"first","affiliation":[{"name":"Lodz University of Technology, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Piotr","family":"Wawrzynkiewicz","sequence":"additional","affiliation":[{"name":"Lodz University of Technology, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joanna","family":"Ochelska-Mierzejewska","sequence":"additional","affiliation":[{"name":"Lodz University of Technology, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"48375","published-online":{"date-parts":[[2025,11,17]]},"reference":[{"key":"ref0","doi-asserted-by":"publisher","unstructured":"[1] Agibetov, A., Blagec, K., Xu, H., Samwald, M.: Fast and scalable neural embedding models for biomedical sentence classification. In: BMC Bioinformatics, Vol. 19, pp. 541 (2018)","DOI":"10.1186\/s12859-018-2496-4"},{"key":"ref1","unstructured":"[2] BigCode Project. bigcode\/the-stack-github-issues. [Online] https:\/\/huggingface.co\/ datasets\/bigcode\/the-stack-github-issues, 2023. Accessed: 10.2024."},{"key":"ref2","unstructured":"[3] Borhan, N., Zulzalil, H., Hassan, S., Mohd Ali, N.: Requirements Prioritization Techniques Focusing on Agile Software Development: A Systematic Literature Review. In: International Journal of Scientific & Technology Research, Vol. 8(11), pp. 2118-2125 (2019)"},{"key":"ref3","unstructured":"[4] Boswell, D.: Introduction to support vector machines. In: Department of Computer Science and Engineering University of California San Diego, Vol. 11, pp. 16-17. (2002)"},{"key":"ref4","doi-asserted-by":"publisher","unstructured":"[5] Brower, H.H., Nicklas, B.J., Nader, M.A., Trost, L.M., Miller, D.P.: Creating effective academic research teams: Two tools borrowed from business practice. In: Journal of Clinical and Translational Science, Vol. 5(1), pp. e74 (2020)","DOI":"10.1017\/cts.2020.553"},{"key":"ref5","doi-asserted-by":"publisher","unstructured":"[6] Chen, Z., Wang, Z., Yang, Y., Gao, J.: Resgraphnet: Graphsage with embedded residual module for prediction of global monthly mean temperature. In: Artificial Intelligence in Geosciences, Vol. 3, pp. 148-156 (2022)","DOI":"10.1016\/j.aiig.2022.11.001"},{"key":"ref6","doi-asserted-by":"publisher","unstructured":"[7] Ciupe, A., Orza, B., Florea, C., Vlaicu, A.: Skill-oriented priority scheduling for solving the resource constrained project scheduling problem. In: IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), Romania, pp. 85-92 (2015)","DOI":"10.1109\/ICCP.2015.7312610"},{"key":"ref7","unstructured":"[8] Fletcher, T.: Support vector machines explained. Tutorial Paper (2009)"},{"key":"ref8","unstructured":"[9] Hugging Face. Hugging face platform. [Online] https:\/\/huggingface.co, 2023. Accessed: 11.2024."},{"key":"ref9","unstructured":"[10] Karabiber. Tf-idf-term frequency-inverse document frequency. [Online] https:\/\/www.learndatasci.com\/glossary\/tf-idf-term, 2020. Accessed: 11.2024."},{"key":"ref10","doi-asserted-by":"publisher","unstructured":"[11] Korytkowski, P., Malachowski, B.: Competence-based estimation of activity duration in it projects. In: European Journal of Operational Research, Vol. 275(2), pp. 708-720 (2019)","DOI":"10.1016\/j.ejor.2018.11.061"},{"key":"ref11","unstructured":"[12] Lefever, Y.: Guesslang: Programming language detection. [Online] https:\/\/github.com\/ yoeo\/guesslang, 2023. Accessed: 11.2024."},{"key":"ref12","doi-asserted-by":"publisher","unstructured":"[13] Lubis, A.R., Nasution, M., Sitompul, O.S., Zamzami, F.M.: The effect of the tf-idf algorithm in time series forecasting for word relevance on social media. In: Indonesian Journal of Electrical Engineering and Computer Science, Vol. 22(2), pp. 976-984 (2021)","DOI":"10.11591\/ijeecs.v22.i2.pp976-984"},{"key":"ref13","unstructured":"[14] Milojevic, D., Macuzic, I., Dordevic, A., Savkovic, M., Dapan, M.: Comparative analysis of software tools for agile project management. In: Quality Festival 2023, ISBN 978-86-6335-104-2 (2023)"},{"key":"ref14","doi-asserted-by":"publisher","unstructured":"[15] Momanyi, B.M., Zhou, Y.W., Grace-Mercure, B.K., Temesgen, S.A., Basharat, A., Ning, L., Tang, L., Gao, H., Lin, H., Tang, H.: SAGESDA: Multi-GraphSAGE networks for predicting SnoRNA-disease associations. In: Current Research in Biomedical Sciences, Vol. 7, pp. 100122 (2024)","DOI":"10.1016\/j.crstbi.2023.100122"},{"key":"ref15","unstructured":"[16] Montgomery, D.C., Peck, E.A., Vining, G.G.: Introduction to linear regression analysis. In: Wiley (2021)"},{"key":"ref16","unstructured":"[17] Priyam, A., Abhijeeta, G.R., Rathee, A., Srivastava, S.: Comparative analysis of decision tree classification algorithms. In: International Journal of Computer Applications, Vol. 3(2), pp. 334-337 (2013)"},{"key":"ref17","doi-asserted-by":"publisher","unstructured":"[18] Qaiser, S., Ali, R.: Text mining: use of TF-IDF to examine the relevance of words to documents. In: Intern. Journal of Computer Applications, Vol. 181(1), pp. 25-29 (2018)","DOI":"10.5120\/ijca2018917395"},{"key":"ref18","unstructured":"[19] Qureshi, H.A., Shah, Y.A.R., Qureshi, S.M., Shah, S.U.R., Shiwlani, A., Ahmad, A.: The promising role of artificial intelligence in navigating lung cancer prognosis. In: International Journal For Multidisciplinary Research, Vol. 6(4), pp. 1-21 (2023)"},{"key":"ref19","doi-asserted-by":"publisher","unstructured":"[20] Riandini, M., Zarlis, M., Situmorang, Z.: Determination of internship location for outstanding students of smk singosari using the k-means clustering algorithm. IN: AIP Conference Proceedings, Vol. 3065(1), pp. 030016 (2024)","DOI":"10.1063\/5.0232749"},{"key":"ref20","unstructured":"[21] Salehinejad, H., Sankar, S., Barfett, J., Colak, E.: Recent advances in recurrent neural networks. In: arXiv preprint arXiv:1801.01078 (2017)"},{"key":"ref21","doi-asserted-by":"publisher","unstructured":"[22] Sarhadi, P., Naeem, W., Fraser, K., Wilson, D.: On the application of agile project management techniques, v-model and recent software tools in postgraduate theses supervision. In: IFAC-PapersOnLine, Vol. 55(17), pp. 109-114 (2022)","DOI":"10.1016\/j.ifacol.2022.09.233"},{"key":"ref22","doi-asserted-by":"publisher","unstructured":"[23] Soroka-Potrzebna, H.: Barriers of knowledge management in virtual project teams: a TISM model. In: Procedia Computer Science, Vol. 207, pp. 800-809 (2022)","DOI":"10.1016\/j.procs.2022.09.135"},{"key":"ref23","doi-asserted-by":"publisher","unstructured":"[24] Suarez-Varela, J., Almasan, P., Ferriol-Galmes, M., Rusek, K., Geyer, F., Cheng, X.: Graph neural networks for communication networks: Context, use cases and opportunities. In: IEEE Network, Vol. 37(3), pp. 146-153 (2022)","DOI":"10.1109\/MNET.123.2100773"},{"key":"ref24","doi-asserted-by":"publisher","unstructured":"[25] Unnikrishnan, R., Kamath, S., Ananthanarayana, V.S.: Benchmarking shallow and deep neural networks for contextual representation of social data. In: Proceedings of 18th India Council International Conference (INDICON), India, pp. 1-8 (2021)","DOI":"10.1109\/INDICON52576.2021.9691551"},{"key":"ref25","unstructured":"[26] Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., Polosukhin, I.: Attention is all you need. In: Proceedings of 31st International Conference on Neural Information Processing Systems, pp. 6000-6010 (2017)"},{"key":"ref26","unstructured":"[27] Velickovic, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., Bengio, Y.: Graph attention networks. In: Proc. of International Conference on Learning Representations (2017)"},{"key":"ref27","doi-asserted-by":"publisher","unstructured":"[28] Vrahatis, A.G., Lazaros, K., Kotsiantis, S: Graph attention networks: A comprehensive review of methods and applications. In: Future Internet, Vol. 16(9), pp. 318 (2024)","DOI":"10.3390\/fi16090318"},{"key":"ref28","doi-asserted-by":"publisher","unstructured":"[29] Wu, L., Chen, Y., Shen, K., Guo, X., and Gao, H., Li, S.: Graph neural networks for natural language processing: A survey. In: IEEE (2023)","DOI":"10.1561\/9781638281436"},{"key":"ref29","doi-asserted-by":"publisher","unstructured":"[30] Zhang, Y., Yu, X., Cui, Z., Wu, S., Wen, Z., Wang, L.: Every document owns its structure: Inductive text classification via graph neural networks. In: arXiv:2004.13826 (2020)","DOI":"10.18653\/v1\/2020.acl-main.31"}],"event":{"name":"33rd International Conference on Information Systems Development","start":{"date-parts":[[2025,9,3]]},"location":"Belgrade, Serbia","end":{"date-parts":[[2025,9,5]]},"acronym":"ISD 2025"},"container-title":["International Conference on Information Systems Development","Proceedings of the 33rd International Conference on Information Systems Development"],"original-title":[],"link":[{"URL":"https:\/\/aisel.aisnet.org\/cgi\/viewcontent.cgi?article=1777&amp;context=isd2014&amp;unstamped=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T17:27:05Z","timestamp":1763573225000},"score":1,"resource":{"primary":{"URL":"https:\/\/aisel.aisnet.org\/isd2014\/proceedings2025\/managingdevops\/3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,17]]},"references-count":30,"URL":"https:\/\/doi.org\/10.62036\/isd.2025.3","relation":{},"ISSN":["2938-5202"],"issn-type":[{"type":"print","value":"2938-5202"}],"subject":[],"published":{"date-parts":[[2025,11,17]]}}}