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Kocoń, Jan; Kanclerz, Kamil; Miłkowski, Piotr; Bojanowski, Bartosz and Zaśko-Zielińska, Monika, 2020, PolEmo 1.0 + MultiEmo-Test 1.0 Multilingual Sentiment Analysis Dataset for KES2020, CLARIN-PL Repository, http://hdl.handle.net/11321/737.
Udostępnij
dc.contributor.authorKocoń, Jan
dc.contributor.authorKanclerz, Kamil
dc.contributor.authorMiłkowski, Piotr
dc.contributor.authorBojanowski, Bartosz
dc.contributor.authorZaśko-Zielińska, Monika
dc.date.accessioned2020-04-02T14:11:13Z
dc.date.available2020-04-02T14:11:13Z
dc.date.issued2020-04-02
dc.descriptionPolEmo 1.0 + MultiEmo-Test 1.0: Corpus of Multi-Domain Consumer Reviews. Test dataset from PolEmo 1.0 was translated to eight different languages: Dutch, English, French, German, Italian, Portuguese, Russian and Spanish. Citation: @article{KANCLERZ2020128, title = {Cross-lingual deep neural transfer learning in sentiment analysis}, journal = {Procedia Computer Science}, volume = {176}, pages = {128-137}, year = {2020}, note = {Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 24th International Conference KES2020}, issn = {1877-0509}, doi = {https://doi.org/10.1016/j.procs.2020.08.014}, url = {https://www.sciencedirect.com/science/article/pii/S187705092031838X}, author = {Kamil Kanclerz and Piotr Miłkowski and Jan Kocoń}, keywords = {natural language processing, sentiment analysis, polarity recognition, transfer learning, deep learning, multilingual approach}, abstract = {In this article, we present a novel technique for the use of language-agnostic sentence representations to adapt the model trained on texts in Polish (as a low-resource language) to recognize polarity in texts in other (high-resource) languages. The first model focuses on the creation of a language-agnostic representation of each sentence. The second one aims to predict the sentiment of the text based on these sentence representations. Besides models evaluation on PolEmo 1.0 Sentiment Corpus, we also conduct a proof of concept for using a deep neural network model trained only on language-agnostic embeddings of texts in Polish to predict the sentiment of the texts in MultiEmo-Test 1.0 Sentiment Corpus, containing PolEmo 1.0 test datasets translated into eight different languages: Dutch, English, French, German, Italian, Portuguese, Russian and Spanish. Both corpora are publicly available under a Creative Commons copyright license.} }
dc.identifier.urihttp://hdl.handle.net/11321/737
dc.language.isopol
dc.language.isoeng
dc.language.isonld
dc.language.isofra
dc.language.isodeu
dc.language.isoita
dc.language.isopor
dc.language.isorus
dc.language.isospa
dc.publisherWrocław University of Science and Technology
dc.rightsCreative Commons - Attribution 4.0 International (CC BY 4.0)
dc.rights.labelCC
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectsentiment
dc.subjectsentiment analysis
dc.subjecttransfer learning
dc.subjectcorpus
dc.subjectmultilingual
dc.titlePolEmo 1.0 + MultiEmo-Test 1.0 Multilingual Sentiment Analysis Dataset for KES2020
dc.typecorpus
local.contact.personJan Kocoń jan.kocon@pwr.edu.pl Wrocław University of Science and Technology
local.files.count2
local.files.size14978081
local.has.filesyes
local.language.namePolish
local.language.nameEnglish
local.language.nameDutch
local.language.nameFrench
local.language.nameGerman
local.language.nameItalian
local.language.namePortuguese
local.language.nameRussian
local.language.nameSpanish
local.size.info60 files
local.size.info32134 entries
local.sponsornationalFunds N/A Ministry of Science and Higher Education (Poland) CLARIN-PL
metashare.ResourceInfo#ContentInfo.mediaTypetext

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