{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T08:31:36Z","timestamp":1761294696023,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031477140"},{"type":"electronic","value":"9783031477157"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-47715-7_56","type":"book-chapter","created":{"date-parts":[[2024,1,29]],"date-time":"2024-01-29T20:02:44Z","timestamp":1706558564000},"page":"841-858","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["End-to-End Aspect Extraction and\u00a0Aspect-Based Sentiment Analysis Framework for\u00a0Low-Resource Languages"],"prefix":"10.1007","author":[{"given":"Georgios","family":"Aivatoglou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexia","family":"Fytili","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Georgios","family":"Arampatzis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dimitrios","family":"Zaikis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nikolaos","family":"Stylianou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ioannis","family":"Vlahavas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,30]]},"reference":[{"issue":"8","key":"56_CR1","doi-asserted-by":"publisher","first-page":"331","DOI":"10.3390\/info12080331","volume":"12","author":"G Alexandridis","year":"2021","unstructured":"Alexandridis, G., Varlamis, I., Korovesis, K., Caridakis, G., Tsantilas, P.: A survey on sentiment analysis and opinion mining in Greek social media. Information 12(8), 331 (2021)","journal-title":"Information"},{"issue":"1","key":"56_CR2","doi-asserted-by":"publisher","first-page":"34","DOI":"10.3390\/a10010034","volume":"10","author":"V Athanasiou","year":"2017","unstructured":"Athanasiou, V., Maragoudakis, M.: A novel, gradient boosting framework for sentiment analysis in languages where nlp resources are not plentiful: a case study for modern greek. Algorithms 10(1), 34 (2017)","journal-title":"Algorithms"},{"key":"56_CR3","doi-asserted-by":"crossref","unstructured":"Conneau, A., Khandelwal, K., Goyal, N., Chaudhary, V., Wenzek, G., Guzm\u00e1n, F., Grave, E., Ott, M., Zettlemoyer, L. and Stoyanov, V.: Unsupervised cross-lingual representation learning at scale (2019). arXiv:1911.02116","DOI":"10.18653\/v1\/2020.acl-main.747"},{"key":"56_CR4","doi-asserted-by":"crossref","unstructured":"Dai, J., Yan, H., Sun, T., Liu, P., Qiu, X.: Does syntax matter? a strong baseline for aspect-based sentiment analysis with roberta (2021). arXiv:2104.04986","DOI":"10.18653\/v1\/2021.naacl-main.146"},{"key":"56_CR5","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding (2018). arXiv:1810.04805"},{"key":"56_CR6","doi-asserted-by":"publisher","unstructured":"Honnibal, M., Montani, I., Van Landeghem, S., Boyd, A.: spacy: Industrial-strength natural language processing in python (2020). https:\/\/doi.org\/10.5281\/zenodo.1212303","DOI":"10.5281\/zenodo.1212303"},{"key":"56_CR7","doi-asserted-by":"crossref","unstructured":"Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proceedings of the tenth ACM Sigkdd International Conference on Knowledge Discovery and Data Mining, pp. 168\u2013177 (2004)","DOI":"10.1145\/1014052.1014073"},{"key":"56_CR8","doi-asserted-by":"crossref","unstructured":"Karimi, A., Rossi, L., Prati, A.: Adversarial training for aspect-based sentiment analysis with Bert. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 8797\u20138803. IEEE (2021)","DOI":"10.1109\/ICPR48806.2021.9412167"},{"key":"56_CR9","doi-asserted-by":"crossref","unstructured":"Kaur, J., Kaur Sidhu, B.: Sentiment analysis based on deep learning approaches. In: 2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 1496\u20131500 IEEE (2018)","DOI":"10.1109\/ICCONS.2018.8662899"},{"key":"56_CR10","doi-asserted-by":"crossref","unstructured":"Korovesis, K., Alexandridis, G., Caridakis, G., Polydoras, P., Tsantilas, P.: Leveraging aspect-based sentiment prediction with textual features and document metadata. In: 11th Hellenic Conference on Artificial Intelligence, pp. 168\u2013174 (2020)","DOI":"10.1145\/3411408.3411433"},{"key":"56_CR11","doi-asserted-by":"crossref","unstructured":"Koutsikakis, J., Chalkidis, I., Malakasiotis, P., Androutsopoulos, I.: Greek-Bert: The Greeks visiting sesame street. In: 11th Hellenic Conference on Artificial Intelligence, pp. 110\u2013117 (2020)","DOI":"10.1145\/3411408.3411440"},{"key":"56_CR12","doi-asserted-by":"crossref","unstructured":"Kv\u00e5lseth, T.O: Note on cohen\u2019s kappa. Psychol. Rep. 65(1), 223\u2013226 (1989)","DOI":"10.2466\/pr0.1989.65.1.223"},{"key":"56_CR13","doi-asserted-by":"publisher","first-page":"46868","DOI":"10.1109\/ACCESS.2020.2978511","volume":"8","author":"X Li","year":"2020","unstructured":"Li, X., Xingyu, F., Guangluan, X., Yang, Y., Wang, J., Jin, L., Liu, Q., Xiang, T.: Enhancing Bert representation with context-aware embedding for aspect-based sentiment analysis. IEEE Access 8, 46868\u201346876 (2020)","journal-title":"IEEE Access"},{"key":"56_CR14","doi-asserted-by":"crossref","unstructured":"Liapakis, A.: A sentiment lexicon-based analysis for food and beverage industry reviews. the Greek language paradigm. The Greek Language Paradigm (2020). Accessed from 20 May 2020","DOI":"10.2139\/ssrn.3606071"},{"key":"56_CR15","unstructured":"Magueresse, A., Carles, V., Heetderks, E.: Low-resource languages: A review of past work and future challenges (2020). arXiv:2006.07264"},{"key":"56_CR16","doi-asserted-by":"crossref","unstructured":"Papineni, K., Roukos, S., Ward, T., Zhu, W.J.: Bleu: a method for automatic evaluation of machine translation. In: Proceedings of the 40th annual meeting of the Association for Computational Linguistics, pp. 311\u2013318 (2002)","DOI":"10.3115\/1073083.1073135"},{"key":"56_CR17","unstructured":"Pavlopoulos, I.: Aspect based sentiment analysis. Athens University of Economics and Business (2014)"},{"key":"56_CR18","doi-asserted-by":"crossref","unstructured":"Pontiki, M., Galanis, D., Papageorgiou, H., Manandhar, S., Androutsopoulos, I. Semeval-2015 task 12: aspect based sentiment analysis. In: Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pp. 486\u2013495 (2015)","DOI":"10.18653\/v1\/S15-2082"},{"key":"56_CR19","doi-asserted-by":"crossref","unstructured":"Sang, E.F., Veenstra, J.: Representing text chunks (1999). cs\/907006","DOI":"10.3115\/977035.977059"},{"key":"56_CR20","doi-asserted-by":"crossref","unstructured":"Solakidis, G.S., Vavliakis, K.N., Mitkas, P.A.: Multilingual sentiment analysis using emoticons and keywords. In: 2014 IEEE\/WIC\/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), vol. 2, pp. 102\u2013109. IEEE (2014)","DOI":"10.1109\/WI-IAT.2014.86"},{"key":"56_CR21","unstructured":"Tiedemann, J.: Parallel data, tools and interfaces in opus. In: Lrec, vol. 2012, pp. 2214\u20132218. Citeseer (2012)"},{"key":"56_CR22","unstructured":"Tiedemann, J., Thottingal, S.: OPUS-MT - Building open translation services for the World. In: Proceedings of the 22nd Annual Conference of the European Association for Machine Translation (EAMT), Lisbon, Portugal (2020)"},{"key":"56_CR23","unstructured":"Wenzek, G., Lachaux, M.A., Conneau, A., Chaudhary, V., Guzman, F., Joulin, A., Grave, E.: Ccnet: Extracting high quality monolingual datasets from web crawl data (2019). arXiv:1911.00359"},{"key":"56_CR24","unstructured":"Xu, H., Liu, B., Shu, L., Yu, P.S.: Bert post-training for review reading comprehension and aspect-based sentiment analysis (2019). arXiv:1904.02232"},{"issue":"4","key":"56_CR25","doi-asserted-by":"publisher","first-page":"919","DOI":"10.1016\/j.dss.2012.12.028","volume":"55","author":"Yu Yang","year":"2013","unstructured":"Yang, Yu., Duan, W., Cao, Q.: The impact of social and conventional media on firm equity value: a sentiment analysis approach. Decis. Supp. Syst. 55(4), 919\u2013926 (2013)","journal-title":"Decis. Supp. Syst."},{"key":"56_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107220","volume":"227","author":"A Zhao","year":"2021","unstructured":"Zhao, A., Yu, Yu.: Knowledge-enabled Bert for aspect-based sentiment analysis. Knowl.-Based Syst. 227, 107220 (2021)","journal-title":"Knowl.-Based Syst."}],"container-title":["Lecture Notes in Networks and Systems","Intelligent Systems and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-47715-7_56","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,29]],"date-time":"2024-01-29T20:09:51Z","timestamp":1706558991000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-47715-7_56"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031477140","9783031477157"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-47715-7_56","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"30 January 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IntelliSys","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Intelligent Systems Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Amsterdam","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"intellisys12023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}