Abstract
This work is about recommending the best journal for article submission to authors. The approach taken here is based on relevance determined through the application of neural network based natural language processing techniques to the abstracts of articles already accepted by journals. Title, keywords, and field of study are not needed in the approach outlined here. The significance of the relevancy of a journal is that an article published in a less relevant journal will have less exposure to the intended target audience, and consequently have less of an impact. The conceptual content contained in the abstracts of articles appearing in a journal can be used to characterize that journal. The main purpose of this work will be exploring neural network architectures for discovering and recommending appropriate journals to those seeking to publish their research. In this work, the current state of the art will be extended and a robust and generic article-to-journal matching tool for all publishers, using Web of Science data, is proposed and made public for the first time.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Aggarwal, A. (2010). Overview and description. isi web of knowledge. Thomson Reuters.
Beel, J., Gipp, B., Langer, S., & Breitinger, C. (2016). paper recommender systems: A literature survey. International Journal on Digital Libraries, 17(4), 305–338.
Larsen, P. O., & Ins, M. V. (2010). The rate of growth in scientific publication and the decline in coverage provided by science citation index. Scientometrics, 84, 575–603.
Wang, D., Liang, Y., Xu, D., Feng, X., & Guan, R. (2018). A content-based recommender system for computer science publications. Knowledge-Based Systems, 157, 1–9. https://doi.org/10.1016/j.knosys.2018.05.001.
Alkan, T. Y., Gunay, M., & Ozbek, F. (2019a). Clustering of scientist using research areas at Akdeniz university. In 2019 IEEE 4th International Conference on Computer Science and Engineering (UBMK) (pp. 1–5).
Alkan, T. Y., Gunay, M., Ozbek, F., San, B. T., & Kitapci, O. (2019b). Assessment of academic performance at Akdeniz university. In Lecture Notes on Data Engineering and Communications Technologies (Vol. 43, pp. 1–5). Artificial Intelligence and Applied Mathematics in Engineering Problems. ICAIAME 2019, Springer.
Cuong, D. V., Nguyen, D. H., Huynh, S., Huynh, P., Gurrin, C., Dao, M.-S., Dang-Nguyen, D.-T., & Nguyen, B. T. (2020). A framework for paper submission recommendation system. In Proceedings of the 2020 International Conference on Multimedia Retrieval, ICMR ’20 (pp. 393–396). Association for Computing Machinery. ISBN 9781450370875. https://doi.org/10.1145/3372278.3391929.
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). Bert: Pre-training of deep bidirectional transformers for language understanding. In NAACL-HLT (pp. 4171–4186).
Horn, F., Arras, L., Montavon, G., Müller, K.-R., & Samek, W. (2017). Exploring text datasets by visualizing relevant words. ArXiv. http://arxiv.org/abs/1707.05261v1.
Lau, J. H., & Baldwin, T. (2016). An empirical evaluation of doc2vec with practical insights into document embedding generation. In Association for Computational Linguistics, Proceedings of the 1st Workshop on Representation Learning for NLP:78-86. https://doi.org/10.18653/v1/W16-1609. https://aclanthology.org/W16-1609.pdf.
Le, Q., & Mikolov, T. (2014). Distributed representations of sentences and documents. In Proceedings of the 31st International Conference on Machine Learning (Vol. 32).
Lilleberg, J., Zhu, Y., & Zhang, Y. (2015). Support vector machines and word2vec for text classification with semantic features. In Proceedings of 2015 IEEE 14th International Conference on Cognitive Informatics and Cognitive Computing. https://doi.org/10.1109/ICCI-CC.2015.7259377.
Medvet, E., Bartoli, A., & Piccinin, G. (2014). Publication venue recommendation based on paper abstract. In 2014 IEEE 26th International Conference on Tools with Artificial Intelligence (pp. 1004–1010). https://doi.org/10.1109/ICTAI.2014.152.
Michail, S., Hazir, U., Alkan, T. Y., Ledet, J. W., & Gunay, M. (2020). A recommendation system for article submission to researcher. In Lecture Notes on Data Engineering and Communications Technologies (Vol. 45, pp. 1–5). Artificial Intelligence and Applied Mathematics in Engineering Problems. ICAIAME 2020, Springer.
Mikolov, T., Chen, K., Corrado, G. S., & Dean, J. (2013a). Efficient estimation of word representations in vector space. https://iclr.cc/archive/2013/workshop-proceedings.html.
Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013b). Distributed representations of words and phrases and their compositionality. In Proceedings of the 26th International Conference on Neural Information Processing Systems (Vol. 2, pp. 3111–3119).
Pennington, J., Socher, R., & Manning, C. D. (2014). GloVe: Global Vectors for Word Representation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) (pp. 1532–1543). https://doi.org/10.3115/v1/D14-1162.
Sanh, V., Debut, L., Chaumond, J., & Wolf, T. (2019). Distilbert, a distilled version of bert: Smaller, faster, cheaper and lighter. ArXiv. http://arxiv.org/abs/1910.01108.
Springer. Journal suggester. https://journalsuggester.springer.com/.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems 30 (NIPS 2017). https://papers.nips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a85aa-bstra ct.html.
Yang, Z., & Davison, B. (2012). Venue recommendation: Submitting your paper with style (pp. 681–686), 12 2012. ISBN 978-1-4673-4651-1. https://doi.org/10.1109/ICMLA.2012.127.
Yüksel, A. S., & Karabiyik, M. A. (2013). Vertical search engine for Academic Publications. In International Conference on Cyber Security and Computer Science.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Michail, S., Ledet, J.W., Alkan, T.Y. et al. A journal recommender for article submission using transformers. Scientometrics 128, 1321–1336 (2023). https://doi.org/10.1007/s11192-022-04609-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11192-022-04609-x