PAVLÍČEK, Martin, Tomáš FILIP a Petr SOSÍK. ZREC architecture for textual sentiment analysis. In Brejová, Broňa; Ciencialová, Lucie; Holeňa, Martin; Mráz, František; Prdubská, Dana; Plátek, Martin; Vinař, Tomáš. Proceedings of the 21st Conference Information Technologies – Applications and Theory (ITAT 2021). 2962. vyd. Slovensko: CEUR Workshop Proceedings. s. 222-228. ISSN 1613-0073. 2021. |
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@inproceedings{54944, author = {Pavlíček, Martin and Filip, Tomáš and Sosík, Petr}, address = {Slovensko}, booktitle = {Proceedings of the 21st Conference Information Technologies – Applications and Theory (ITAT 2021)}, edition = {2962}, editor = {Brejová, Broňa; Ciencialová, Lucie; Holeňa, Martin; Mráz, František; Prdubská, Dana; Plátek, Martin; Vinař, Tomáš}, keywords = {Bio-inspired computing; Computing methods; Data gathering; Pipeline solutions; Relation extraction; Sentiment analysis}, howpublished = {elektronická verze "online"}, language = {eng}, location = {Slovensko}, pages = {222-228}, publisher = {CEUR Workshop Proceedings}, title = {ZREC architecture for textual sentiment analysis}, url = {http://ceur-ws.org/Vol-2962/paper48.pdf}, year = {2021} }
TY - JOUR ID - 54944 AU - Pavlíček, Martin - Filip, Tomáš - Sosík, Petr PY - 2021 TI - ZREC architecture for textual sentiment analysis PB - CEUR Workshop Proceedings CY - Slovensko KW - Bio-inspired computing KW - Computing methods KW - Data gathering KW - Pipeline solutions KW - Relation extraction KW - Sentiment analysis UR - http://ceur-ws.org/Vol-2962/paper48.pdf N2 - We present recent results of the research project ZREC aimed at psycho-social phenomena (group polarization, belief echo chamber and confirmatory bias) analysis based on bio-inspired computing methods. We present two updated pipeline solutions to work with bio inspired AI methods and data gathering tools integrated in a complex (but simple to implement) vertical information system. The scope of the investigated phenomena is reduced to the aspect based sentiment analysis with an integration of methods covering named entity recognition and relation extraction. We present a simple ontology addition to group polarization in the last year due to COVID pandemic and stress the importance of project in the social and IT sphere and multi-tier cooperation. We also provide introductory results based on test data using several deep learning architectures and demonstrating that the presented approach is robust and functional. ER -
PAVLÍČEK, Martin, Tomáš FILIP a Petr SOSÍK. ZREC architecture for textual sentiment analysis. In Brejová, Broňa; Ciencialová, Lucie; Holeňa, Martin; Mráz, František; Prdubská, Dana; Plátek, Martin; Vinař, Tomáš. \textit{Proceedings of the 21st Conference Information Technologies – Applications and Theory (ITAT 2021)}. 2962. vyd. Slovensko: CEUR Workshop Proceedings. s.~222-228. ISSN~1613-0073. 2021.
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