Word embedding (Portuguese Wikipedia)
Analysis of information sources in references of the Wikipedia article "Word embedding" in Portuguese language version.
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aaai.org
ojs.aaai.org
- Rabii, Younès; Cook, Michael (4 de outubro de 2021). «Revealing Game Dynamics via Word Embeddings of Gameplay Data». Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (em inglês). 17 (1): 187–194. ISSN 2334-0924. doi:10.1609/aiide.v17i1.18907
aclanthology.org
- Devlin, Jacob; Chang, Ming-Wei; Lee, Kenton; Toutanova, Kristina (julho de 2019). «Proceedings of the 2019 Conference of the North». Association for Computational Linguistics. 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): 4171–4186. doi:10.18653/v1/N19-1423
aclweb.org
- Reisinger, Joseph; Mooney, Raymond J. (2010). Multi-Prototype Vector-Space Models of Word Meaning. Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics. Los Angeles, California: Association for Computational Linguistics. pp. 109–117. ISBN 978-1-932432-65-7. Consultado em 25 de outubro de 2019
- Akbik, Alan; Blythe, Duncan; Vollgraf, Roland (2018). «Contextual String Embeddings for Sequence Labeling». Santa Fe, New Mexico, USA: Association for Computational Linguistics. Proceedings of the 27th International Conference on Computational Linguistics: 1638–1649
allennlp.org
arxiv.org
- Mikolov, Tomas; Sutskever, Ilya. «Distributed Representations of Words and Phrases and their Compositionality». arXiv:1310.4546 [cs.CL]
- Lebret, Rémi; Collobert, Ronan (2013). «Word Emdeddings through Hellinger PCA». Conference of the European Chapter of the Association for Computational Linguistics (EACL). 2014. [S.l.: s.n.] arXiv:1312.5542
- Qureshi, M. Atif; Greene, Derek (4 de junho de 2018). «EVE: explainable vector based embedding technique using Wikipedia». Journal of Intelligent Information Systems (em inglês). 53: 137–165. ISSN 0925-9902. arXiv:1702.06891. doi:10.1007/s10844-018-0511-x
- Camacho-Collados, Jose; Pilehvar, Mohammad Taher. «From Word to Sense Embeddings: A Survey on Vector Representations of Meaning». arXiv:1805.04032 [cs.CL]
- Neelakantan, Arvind; Shankar, Jeevan; Passos, Alexandre; McCallum, Andrew (2014). «Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space». Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). Stroudsburg, PA, USA: Association for Computational Linguistics. pp. 1059–1069. arXiv:1504.06654. doi:10.3115/v1/d14-1113
- Ruas, Terry; Grosky, William; Aizawa, Akiko (1 de dezembro de 2019). «Multi-sense embeddings through a word sense disambiguation process». Expert Systems with Applications. 136: 288–303. ISSN 0957-4174. arXiv:2101.08700. doi:10.1016/j.eswa.2019.06.026
- Li, Jiwei; Jurafsky, Dan (2015). «Do Multi-Sense Embeddings Improve Natural Language Understanding?». Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics. pp. 1722–1732. arXiv:1506.01070. doi:10.18653/v1/d15-1200
- Asgari, Ehsaneddin; Mofrad, Mohammad R.K. (2015). «Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics». PLOS ONE. 10 (11): e0141287. Bibcode:2015PLoSO..1041287A. PMC 4640716. PMID 26555596. arXiv:1503.05140. doi:10.1371/journal.pone.0141287
- Kiros, Ryan; Zhu, Yukun. «skip-thought vectors». arXiv:1506.06726 [cs.CL]
- Zhao, Jieyu; et al. (2018). «Learning Gender-Neutral Word Embeddings». arXiv:1809.01496 [cs.CL]
- Pires, Telmo; Schlinger, Eva (4 de junho de 2019). «How multilingual is Multilingual BERT?». arXiv:1906.01502 [cs.CL]
- Bolukbasi, Tolga; Chang, Kai-Wei (2016). «Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings». arXiv:1607.06520 [cs.CL]
- Bolukbasi, Tolga; Chang, Kai-Wei (21 de julho de 2016). «Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings». arXiv:1607.06520 [cs.CL]
- Dieng, Adji B.; Ruiz, Francisco J. R.; Blei, David M. (2020). «Topic Modeling in Embedding Spaces». Transactions of the Association for Computational Linguistics. 8: 439–453. arXiv:1907.04907. doi:10.1162/tacl_a_00325
code.google.com
- «word2vec». Google Code Archive. Consultado em 23 de julho de 2021
doi.org
dx.doi.org
- Qureshi, M. Atif; Greene, Derek (4 de junho de 2018). «EVE: explainable vector based embedding technique using Wikipedia». Journal of Intelligent Information Systems (em inglês). 53: 137–165. ISSN 0925-9902. arXiv:1702.06891. doi:10.1007/s10844-018-0511-x
- Luhn, H.P. (1953). «A New Method of Recording and Searching Information». American Documentation. 4: 14–16. doi:10.1002/asi.5090040104
- Salton, Gerard (1962). «Some experiments in the generation of word and document associations». Proceedings of the December 4-6, 1962, fall joint computer conference on - AFIPS '62 (Fall). [S.l.: s.n.] pp. 234–250. ISBN 9781450378796. doi:10.1145/1461518.1461544
- Salton, Gerard; Wong, A; Yang, C S (1975). «A Vector Space Model for Automatic Indexing». Communications of the ACM. 18 (11): 613–620. doi:10.1145/361219.361220
- Bengio, Yoshua; Schwenk, Holger; Senécal, Jean-Sébastien; Morin, Fréderic; Gauvain, Jean-Luc (2006). «A Neural Probabilistic Language Model». Studies in Fuzziness and Soft Computing. 194. [S.l.]: Springer. pp. 137–186. ISBN 978-3-540-30609-2. doi:10.1007/3-540-33486-6_6
- Lavelli, Alberto; Sebastiani, Fabrizio; Zanoli, Roberto (2004). Distributional term representations: an experimental comparison. 13th ACM International Conference on Information and Knowledge Management. pp. 615–624. doi:10.1145/1031171.1031284
- Roweis, Sam T.; Saul, Lawrence K. (2000). «Nonlinear Dimensionality Reduction by Locally Linear Embedding». Science. 290 (5500): 2323–6. Bibcode:2000Sci...290.2323R. CiteSeerX 10.1.1.111.3313. PMID 11125150. doi:10.1126/science.290.5500.2323
- Neelakantan, Arvind; Shankar, Jeevan; Passos, Alexandre; McCallum, Andrew (2014). «Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space». Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). Stroudsburg, PA, USA: Association for Computational Linguistics. pp. 1059–1069. arXiv:1504.06654. doi:10.3115/v1/d14-1113
- Ruas, Terry; Grosky, William; Aizawa, Akiko (1 de dezembro de 2019). «Multi-sense embeddings through a word sense disambiguation process». Expert Systems with Applications. 136: 288–303. ISSN 0957-4174. arXiv:2101.08700. doi:10.1016/j.eswa.2019.06.026
- Agre, Gennady; Petrov, Daniel; Keskinova, Simona (1 de março de 2019). «Word Sense Disambiguation Studio: A Flexible System for WSD Feature Extraction». Information (em inglês). 10 (3). 97 páginas. ISSN 2078-2489. doi:10.3390/info10030097
- Li, Jiwei; Jurafsky, Dan (2015). «Do Multi-Sense Embeddings Improve Natural Language Understanding?». Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics. pp. 1722–1732. arXiv:1506.01070. doi:10.18653/v1/d15-1200
- Devlin, Jacob; Chang, Ming-Wei; Lee, Kenton; Toutanova, Kristina (julho de 2019). «Proceedings of the 2019 Conference of the North». Association for Computational Linguistics. 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): 4171–4186. doi:10.18653/v1/N19-1423
- Asgari, Ehsaneddin; Mofrad, Mohammad R.K. (2015). «Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics». PLOS ONE. 10 (11): e0141287. Bibcode:2015PLoSO..1041287A. PMC 4640716. PMID 26555596. arXiv:1503.05140. doi:10.1371/journal.pone.0141287
- Rabii, Younès; Cook, Michael (4 de outubro de 2021). «Revealing Game Dynamics via Word Embeddings of Gameplay Data». Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (em inglês). 17 (1): 187–194. ISSN 2334-0924. doi:10.1609/aiide.v17i1.18907
- Ghassemi, Mohammad; Mark, Roger; Nemati, Shamim (2015). «A visualization of evolving clinical sentiment using vector representations of clinical notes». 2015 Computing in Cardiology Conference (CinC). 2015. [S.l.: s.n.] pp. 629–632. ISBN 978-1-5090-0685-4. PMC 5070922. PMID 27774487. doi:10.1109/CIC.2015.7410989
- Dieng, Adji B.; Ruiz, Francisco J. R.; Blei, David M. (2020). «Topic Modeling in Embedding Spaces». Transactions of the Association for Computational Linguistics. 8: 439–453. arXiv:1907.04907. doi:10.1162/tacl_a_00325
- Zhao, Jieyu; Wang, Tianlu; Yatskar, Mark; Ordonez, Vicente; Chang, Kai-Wei (2017). «Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints». Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. [S.l.: s.n.] pp. 2979–2989. doi:10.18653/v1/D17-1323
- Petreski, Davor; Hashim, Ibrahim C. (26 de maio de 2022). «Word embeddings are biased. But whose bias are they reflecting?». AI & Society (em inglês). 38 (2): 975–982. ISSN 1435-5655. doi:10.1007/s00146-022-01443-w
escholarship.org
cloudfront.escholarship.org
- Kanerva, Pentti, Kristoferson, Jan and Holst, Anders (2000): Random Indexing of Text Samples for Latent Semantic Analysis, Proceedings of the 22nd Annual Conference of the Cognitive Science Society, p. 1036. Mahwah, New Jersey: Erlbaum, 2000.
files.wordpress.com
levyomer.files.wordpress.com
- Levy, Omer; Goldberg, Yoav (2014). Linguistic Regularities in Sparse and Explicit Word Representations (PDF). CoNLL. pp. 171–180
googleusercontent.com
static.googleusercontent.com
- Globerson, Amir (2007). «Euclidean Embedding of Co-occurrence Data» (PDF). Journal of Machine Learning Research
harvard.edu
ui.adsabs.harvard.edu
- Roweis, Sam T.; Saul, Lawrence K. (2000). «Nonlinear Dimensionality Reduction by Locally Linear Embedding». Science. 290 (5500): 2323–6. Bibcode:2000Sci...290.2323R. CiteSeerX 10.1.1.111.3313. PMID 11125150. doi:10.1126/science.290.5500.2323
- Asgari, Ehsaneddin; Mofrad, Mohammad R.K. (2015). «Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics». PLOS ONE. 10 (11): e0141287. Bibcode:2015PLoSO..1041287A. PMC 4640716. PMID 26555596. arXiv:1503.05140. doi:10.1371/journal.pone.0141287
ijcai.org
- Li, Yitan; Xu, Linli (2015). Word Embedding Revisited: A New Representation Learning and Explicit Matrix Factorization Perspective (PDF). Int'l J. Conf. on Artificial Intelligence (IJCAI)
jmlr.org
- Bengio, Yoshua; Ducharme, Réjean; Vincent, Pascal; Jauvin, Christian (2003). «A Neural Probabilistic Language Model» (PDF). Journal of Machine Learning Research. 3: 1137–1155
linkedin.com
- Sahlgren, Magnus. «A brief history of word embeddings»
mit.edu
direct.mit.edu
- Dieng, Adji B.; Ruiz, Francisco J. R.; Blei, David M. (2020). «Topic Modeling in Embedding Spaces». Transactions of the Association for Computational Linguistics. 8: 439–453. arXiv:1907.04907. doi:10.1162/tacl_a_00325
neurips.cc
proceedings.neurips.cc
- Bengio, Yoshua; Réjean, Ducharme; Pascal, Vincent (2000). «A Neural Probabilistic Language Model» (PDF). NeurIPS
- Vinkourov, Alexei; Cristianini, Nello; Shawe-Taylor, John (2002). Inferring a semantic representation of text via cross-language correlation analysis. (PDF). Advances in Neural Information Processing Systems. 15
nih.gov
ncbi.nlm.nih.gov
- Roweis, Sam T.; Saul, Lawrence K. (2000). «Nonlinear Dimensionality Reduction by Locally Linear Embedding». Science. 290 (5500): 2323–6. Bibcode:2000Sci...290.2323R. CiteSeerX 10.1.1.111.3313. PMID 11125150. doi:10.1126/science.290.5500.2323
- Asgari, Ehsaneddin; Mofrad, Mohammad R.K. (2015). «Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics». PLOS ONE. 10 (11): e0141287. Bibcode:2015PLoSO..1041287A. PMC 4640716. PMID 26555596. arXiv:1503.05140. doi:10.1371/journal.pone.0141287
- Ghassemi, Mohammad; Mark, Roger; Nemati, Shamim (2015). «A visualization of evolving clinical sentiment using vector representations of clinical notes». 2015 Computing in Cardiology Conference (CinC). 2015. [S.l.: s.n.] pp. 629–632. ISBN 978-1-5090-0685-4. PMC 5070922. PMID 27774487. doi:10.1109/CIC.2015.7410989
nips.cc
papers.nips.cc
- Levy, Omer; Goldberg, Yoav (2014). Neural Word Embedding as Implicit Matrix Factorization (PDF). NIPS
- Mnih, Andriy; Hinton, Geoffrey (2009). «A Scalable Hierarchical Distributed Language Model». Curran Associates, Inc. Advances in Neural Information Processing Systems. 21 (NIPS 2008): 1081–1088
psu.edu
citeseerx.ist.psu.edu
- Roweis, Sam T.; Saul, Lawrence K. (2000). «Nonlinear Dimensionality Reduction by Locally Linear Embedding». Science. 290 (5500): 2323–6. Bibcode:2000Sci...290.2323R. CiteSeerX 10.1.1.111.3313. PMID 11125150. doi:10.1126/science.290.5500.2323
radimrehurek.com
sics.se
eprints.sics.se
- Sahlgren, Magnus (2005) An Introduction to Random Indexing, Proceedings of the Methods and Applications of Semantic Indexing Workshop at the 7th International Conference on Terminology and Knowledge Engineering, TKE 2005, August 16, Copenhagen, Denmark
- Sahlgren, Magnus, Holst, Anders and Pentti Kanerva (2008) Permutations as a Means to Encode Order in Word Space, In Proceedings of the 30th Annual Conference of the Cognitive Science Society: 1300–1305.
socher.org
- Socher, Richard; Bauer, John; Manning, Christopher; Ng, Andrew (2013). Parsing with compositional vector grammars (PDF). Proc. ACL Conf. Consultado em 14 de agosto de 2014. Cópia arquivada (PDF) em 11 de agosto de 2016
stanford.edu
nlp.stanford.edu
- Socher, Richard; Perelygin, Alex; Wu, Jean; Chuang, Jason; Manning, Chris; Ng, Andrew; Potts, Chris (2013). Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank (PDF). EMNLP
- «GloVe»
web.stanford.edu
- Jurafsky, Daniel; H. James, Martin (2000). Speech and language processing : an introduction to natural language processing, computational linguistics, and speech recognition. Upper Saddle River, N.J.: Prentice Hall. ISBN 978-0-13-095069-7
thefreelibrary.com
- Dubin, David (2004). «The most influential paper Gerard Salton never wrote.». Consultado em 18 de outubro de 2020. Arquivado do original em 18 de outubro de 2020
web.archive.org
- Socher, Richard; Bauer, John; Manning, Christopher; Ng, Andrew (2013). Parsing with compositional vector grammars (PDF). Proc. ACL Conf. Consultado em 14 de agosto de 2014. Cópia arquivada (PDF) em 11 de agosto de 2016
- Dubin, David (2004). «The most influential paper Gerard Salton never wrote.». Consultado em 18 de outubro de 2020. Arquivado do original em 18 de outubro de 2020
wikipedia.org
he.wikipedia.org
worldcat.org
- Qureshi, M. Atif; Greene, Derek (4 de junho de 2018). «EVE: explainable vector based embedding technique using Wikipedia». Journal of Intelligent Information Systems (em inglês). 53: 137–165. ISSN 0925-9902. arXiv:1702.06891. doi:10.1007/s10844-018-0511-x
- Huang, Eric. (2012). Improving word representations via global context and multiple word prototypes. [S.l.: s.n.] OCLC 857900050
- Ruas, Terry; Grosky, William; Aizawa, Akiko (1 de dezembro de 2019). «Multi-sense embeddings through a word sense disambiguation process». Expert Systems with Applications. 136: 288–303. ISSN 0957-4174. arXiv:2101.08700. doi:10.1016/j.eswa.2019.06.026
- Agre, Gennady; Petrov, Daniel; Keskinova, Simona (1 de março de 2019). «Word Sense Disambiguation Studio: A Flexible System for WSD Feature Extraction». Information (em inglês). 10 (3). 97 páginas. ISSN 2078-2489. doi:10.3390/info10030097
- Rabii, Younès; Cook, Michael (4 de outubro de 2021). «Revealing Game Dynamics via Word Embeddings of Gameplay Data». Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (em inglês). 17 (1): 187–194. ISSN 2334-0924. doi:10.1609/aiide.v17i1.18907
- Petreski, Davor; Hashim, Ibrahim C. (26 de maio de 2022). «Word embeddings are biased. But whose bias are they reflecting?». AI & Society (em inglês). 38 (2): 975–982. ISSN 1435-5655. doi:10.1007/s00146-022-01443-w