{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:12:01Z","timestamp":1742911921867,"version":"3.40.3"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030665265"},{"type":"electronic","value":"9783030665272"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-66527-2_19","type":"book-chapter","created":{"date-parts":[[2020,12,30]],"date-time":"2020-12-30T18:04:51Z","timestamp":1609351491000},"page":"256-270","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards the Evaluation of Feature Embedding Models of the Fusional Languages"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2589-9900","authenticated-orcid":false,"given":"Alina","family":"Wr\u00f3blewska","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katarzyna","family":"Krasnowska-Kiera\u015b","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Piotr","family":"Rybak","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,12,31]]},"reference":[{"key":"19_CR1","unstructured":"Andor, D., et al.: Globally normalized transition-based neural networks. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 2442\u20132452. Association for Computational Linguistics, Berlin (2016). https:\/\/www.aclweb.org\/anthology\/P16-1231"},{"key":"19_CR2","unstructured":"Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate (2014). http:\/\/arxiv.org\/abs\/1409.0473"},{"key":"19_CR3","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1162\/tacl_a_00051","volume":"5","author":"P Bojanowski","year":"2017","unstructured":"Bojanowski, P., Grave, E., Joulin, A., Mikolov, T.: Enriching word vectors with subword information. Trans. Assoc. Comput. Linguist. 5, 135\u2013146 (2017). https:\/\/www.aclweb.org\/anthology\/Q17-1010","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"19_CR4","unstructured":"Chen, D., Manning, C.: A fast and accurate dependency parser using neural networks. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 740\u2013750. Association for Computational Linguistics, Doha (2014). https:\/\/www.aclweb.org\/anthology\/D14-1082"},{"key":"19_CR5","unstructured":"Chiu, B., Korhonen, A., Pyysalo, S.: Intrinsic evaluation of word vectors fails to predict extrinsic performance. In: Proceedings of the 1st Workshop on Evaluating Vector-Space Representations for NLP, pp. 1\u20136. Association for Computational Linguistics, Berlin (2016). https:\/\/www.aclweb.org\/anthology\/W16-2501"},{"key":"19_CR6","unstructured":"Cho, K., et al.: Learning phrase representations using RNN encoder-decoder for statistical machine translation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1724\u20131734. Association for Computational Linguistics, Doha (2014). https:\/\/www.aclweb.org\/anthology\/D14-1179"},{"key":"19_CR7","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 4171\u20134186. Association for Computational Linguistics, Minneapolis (2019). https:\/\/www.aclweb.org\/anthology\/N19-1423"},{"key":"19_CR8","unstructured":"Dozat, T., Qi, P., Manning, C.D.: Stanford\u2019s graph-based neural dependency parser at the CoNLL 2017 shared task. In: Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pp. 20\u201330. Association for Computational Linguistics, Vancouver (2017). https:\/\/www.aclweb.org\/anthology\/K17-3002"},{"key":"19_CR9","unstructured":"Drozd, A., Gladkova, A., Matsuoka, S.: Word embeddings, analogies, and machine learning: beyond king$$-$$man$$+$$woman$$=$$queen. In: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pp. 3519\u20133530. The COLING 2016 Organizing Committee, Osaka (2016). https:\/\/www.aclweb.org\/anthology\/C16-1332"},{"key":"19_CR10","unstructured":"Faruqui, M., Tsvetkov, Y., Rastogi, P., Dyer, C.: Problems with evaluation of word embeddings using word similarity tasks. In: Proceedings of the 1st Workshop on Evaluating Vector-Space Representations for NLP, pp. 30\u201335. Association for Computational Linguistics, Berlin (2016). https:\/\/www.aclweb.org\/anthology\/W16-2506"},{"issue":"1","key":"19_CR11","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1145\/503104.503110","volume":"20","author":"L Finkelstein","year":"2002","unstructured":"Finkelstein, L., et al.: Placing search in context: the concept revisited. ACM Trans. Inf. Syst. 20(1), 116\u2013131 (2002). https:\/\/doi.org\/10.1145\/503104.503110","journal-title":"ACM Trans. Inf. Syst."},{"key":"19_CR12","unstructured":"Grave, E., Bojanowski, P., Gupta, P., Joulin, A., Mikolov, T.: Learning word vectors for 157 languages. In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). European Language Resources Association (ELRA), Miyazaki (2018). https:\/\/www.aclweb.org\/anthology\/L18-1550"},{"issue":"4","key":"19_CR13","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1162\/COLI_a_00237","volume":"41","author":"F Hill","year":"2015","unstructured":"Hill, F., Reichart, R., Korhonen, A.: SimLex-999: evaluating semantic models with (genuine) similarity estimation. Computat. Linguist. 41(4), 665\u2013695 (2015). https:\/\/www.aclweb.org\/anthology\/J15-4004","journal-title":"Computat. Linguist."},{"key":"19_CR14","unstructured":"Iyyer, M., Manjunatha, V., Boyd-Graber, J., Daum\u00e9 III, H.: Deep unordered composition rivals syntactic methods for text classification. In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 1681\u20131691. Association for Computational Linguistics, Beijing (2015). https:\/\/www.aclweb.org\/anthology\/P15-1162"},{"key":"19_CR15","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1162\/tacl_a_00101","volume":"4","author":"E Kiperwasser","year":"2016","unstructured":"Kiperwasser, E., Goldberg, Y.: Simple and accurate dependency parsing using bidirectional lstm feature representations. Trans. Assoc. Comput. Linguist. 4, 313\u2013327 (2016). https:\/\/www.aclweb.org\/anthology\/Q16-1023","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"19_CR16","doi-asserted-by":"crossref","unstructured":"Kobyli\u0144ski, \u0141., Kiera\u015b, W.: Part of speech tagging for polish: state of the art and future perspectives. In: Proceedings of Computational Linguistics and Intelligent Text Processing, pp. 307\u2013319 (2016)","DOI":"10.1007\/978-3-319-75477-2_21"},{"key":"19_CR17","unstructured":"Kobyli\u0144ski, \u0141., Ogrodniczuk, M.: Results of the PolEval 2017 competition: part-of-speech tagging shared task. In: Vetulani, Z., Paroubek, P. (eds.) Proceedings of the 8th Language & Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics, pp. 362\u2013366. Fundacja Uniwersytetu im. Adama Mickiewicza w Poznaniu, Pozna\u0144 (2017)"},{"key":"19_CR18","unstructured":"Krasnowska-Kiera\u015b, K.: Morphosyntactic disambiguation for Polish with bi-LSTM neural networks. In: Vetulani, Z., Paroubek, P. (eds.) Proceedings of the 8th Language & Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics, pp. 367\u2013371. Fundacja Uniwersytetu im. Adama Mickiewicza w Poznaniu, Pozna\u0144 (2017). http:\/\/ltc.amu.edu.pl\/book2017\/papers\/PolEval1-2.pdf"},{"key":"19_CR19","unstructured":"Leviant, I., Reichart, R.: Separated by an un-common language: towards judgment language informed vector space modeling. CoRR abs\/1508.00106 (2015). http:\/\/arxiv.org\/abs\/1508.00106"},{"key":"19_CR20","unstructured":"Linzen, T.: Issues in evaluating semantic spaces using word analogies. In: Proceedings of the 1st Workshop on Evaluating Vector-Space Representations for NLP, pp. 13\u201318. Association for Computational Linguistics, Berlin (2016). https:\/\/www.aclweb.org\/anthology\/W16-2503"},{"key":"19_CR21","unstructured":"Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Burges, C.J.C., Bottou, L., Welling, M., Ghahramani, Z., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems, vol. 26, pp. 3111\u20133119. Curran Associates, Inc. (2013). http:\/\/papers.nips.cc\/paper\/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf"},{"key":"19_CR22","unstructured":"Mikolov, T., Yih, W.t., Zweig, G.: Linguistic regularities in continuous space word representations. In: Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 746\u2013751. Association for Computational Linguistics, Atlanta (2013). https:\/\/www.aclweb.org\/anthology\/N13-1090"},{"key":"19_CR23","unstructured":"Mykowiecka, A., Marciniak, M., Rychlik, P.: Testing word embeddings for Polish. Cogn. Stud.\/\u00c9tudes Cogn. 17, 1\u201319 (2017). https:\/\/ispan.waw.pl\/journals\/index.php\/cs-ec\/article\/view\/cs.1468"},{"key":"19_CR24","unstructured":"Nivre, J., Hall, J., Nilsson, J.: MaltParser: a data-driven parser-generator for dependency parsing. In: Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC 2006), pp. 2216\u20132219. European Language Resources Association (ELRA), Genoa (2006). http:\/\/www.lrec-conf.org\/proceedings\/lrec2006\/pdf\/162_pdf.pdf"},{"key":"19_CR25","unstructured":"Pennington, J., Socher, R., Manning, C.: GloVe: global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532\u20131543. Association for Computational Linguistics, Doha (2014). https:\/\/www.aclweb.org\/anthology\/D14-1162"},{"key":"19_CR26","unstructured":"Przepi\u00f3rkowski, A., Ba\u0144ko, M., G\u00f3rski, R.L., Lewandowska-Tomaszczyk, B. (eds.): Narodowy Korpus J\u0119zyka Polskiego. Wydawnictwo Naukowe PWN, Warsaw (2012)"},{"key":"19_CR27","unstructured":"\u0158eh\u016f\u0159ek, R., Sojka, P.: Software framework for topic modelling with large corpora. In: Proceedings of the Workshop on New Challenges for NLP Frameworks, pp. 45\u201350 (2010)"},{"key":"19_CR28","unstructured":"Rybak, P., Wr\u00f3blewska, A.: Semi-supervised neural system for tagging, parsing and lematization. In: Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pp. 45\u201354. Association for Computational Linguistics, Brussels (2018). https:\/\/www.aclweb.org\/anthology\/K18-2004"},{"key":"19_CR29","unstructured":"Sutskever, I., Vinyals, O., Le, Q.V.: Sequence to sequence learning with neural networks. In: Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N.D., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems, vol. 27, pp. 3104\u20133112. Curran Associates, Inc. (2014). http:\/\/papers.nips.cc\/paper\/5346-sequence-to-sequence-learning-with-neural-networks.pdf"},{"key":"19_CR30","unstructured":"Vuli\u0107, I., Mrk\u0161i\u0107, N., Reichart, R., \u00d3 S\u00e9aghdha, D., Young, S., Korhonen, A.: Morph-fitting: fine-tuning word vector spaces with simple language-specific rules. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 56\u201368. Association for Computational Linguistics, Vancouver (2017). https:\/\/www.aclweb.org\/anthology\/P17-1006"},{"key":"19_CR31","unstructured":"Wr\u00f3blewska, A.: Polish dependency parser trained on an automatically induced dependency bank. Ph.D. dissertation, ICS PAS, Warsaw (2014)"},{"issue":"2","key":"19_CR32","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1515\/psicl-2019-0012","volume":"55","author":"A Wr\u00f3blewska","year":"2019","unstructured":"Wr\u00f3blewska, A., Rybak, P.: Dependency Parsing of Polish. Pozna\u0144 Stud. Contemp. Linguist. 55(2), 305\u2013337 (2019). https:\/\/doi.org\/10.1515\/psicl-2019-0012","journal-title":"Pozna\u0144 Stud. Contemp. Linguist."}],"container-title":["Lecture Notes in Computer Science","Human Language Technology. Challenges for Computer Science and Linguistics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-66527-2_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,30]],"date-time":"2020-12-30T18:12:47Z","timestamp":1609351967000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-66527-2_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030665265","9783030665272"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-66527-2_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"31 December 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"LTC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Language and Technology Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pozna\u0144","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Poland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 November 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 November 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ltconf2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ltc.amu.edu.pl\/a2017\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"97","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"26","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"27% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}