Word2vec (Spanish Wikipedia)

Analysis of information sources in references of the Wikipedia article "Word2vec" in Spanish language version.

refsWebsite

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9arxiv.org

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5doi.org

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3nih.gov

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2harvard.edu

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2aclweb.org

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1towardsdatascience.com

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1code.google.com

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1groups.google.com

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1mit.edu

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1medium.com

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1github.com

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1web.archive.org

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1deeplearning4j.org

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1radimrehurek.com

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1semanticscholar.org

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aclweb.org

Levy, Omer; Goldberg, Yoav; Dagan, Ido (2015). «Improving Distributional Similarity with Lessons Learned from Word Embeddings». Transactions of the Association for Computational Linguistics (Transactions of the Association for Computational Linguistics) 3: 211-225. doi:10.1162/tacl_a_00134.
Arora, S (Summer 2016). «A Latent Variable Model Approach to PMI-based Word Embeddings». Transactions of the Association for Computational Linguistics 4: 385-399. doi:10.1162/tacl_a_00106 – vía ACLWEB.

arxiv.org

Mikolov, Tomas (2013). «Efficient Estimation of Word Representations in Vector Space». arXiv:1301.3781 [cs.CL].
Mikolov, Tomas (2013). «Efficient Estimation of Word Representations in Vector Space». arXiv:1301.3781 [cs.CL].
Mikolov, Tomas (2013). «Distributed representations of words and phrases and their compositionality.». Advances in Neural Information Processing Systems. arXiv:1310.4546.
Goldberg, Yoav; Levy, Omer (2014). «word2vec Explained: Deriving Mikolov et al.'s Negative-Sampling Word-Embedding Method». arXiv:1402.3722 [cs.CL].
Mikolov, Tomas; Sutskever, Ilya; Chen, Kai; Corrado, Greg S.; Dean, Jeff (2013). Distributed representations of words and phrases and their compositionality. Advances in Neural Information Processing Systems. Bibcode:2013arXiv1310.4546M. arXiv:1310.4546.
Le, Quoc (2014). «Distributed Representations of Sentences and Documents.». arXiv:1405.4053 [cs.CL].
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.
Ng, Patrick (2017). «dna2vec: Consistent vector representations of variable-length k-mers». arXiv:1701.06279 [q-bio.QM].
Altszyler, E.; Ribeiro, S.; Sigman, M.; Fernández Slezak, D. (2017). «The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text». Consciousness and Cognition 56: 178-187. PMID 28943127. S2CID 195347873. arXiv:1610.01520. doi:10.1016/j.concog.2017.09.004.

code.google.com

«Google Code Archive - Long-term storage for Google Code Project Hosting.». code.google.com. Consultado el 13 de junio de 2016.

deeplearning4j.org

«Doc2Vec and Paragraph Vectors for Classification». Archivado desde el original el 31 de diciembre de 2015. Consultado el 13 de enero de 2016.

doi.org

dx.doi.org

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.
Banerjee, Imon; Chen, Matthew C.; Lungren, Matthew P.; Rubin, Daniel L. (2018). «Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort». Journal of Biomedical Informatics 77: 11-20. PMC 5771955. PMID 29175548. doi:10.1016/j.jbi.2017.11.012.
Levy, Omer; Goldberg, Yoav; Dagan, Ido (2015). «Improving Distributional Similarity with Lessons Learned from Word Embeddings». Transactions of the Association for Computational Linguistics (Transactions of the Association for Computational Linguistics) 3: 211-225. doi:10.1162/tacl_a_00134.
Arora, S (Summer 2016). «A Latent Variable Model Approach to PMI-based Word Embeddings». Transactions of the Association for Computational Linguistics 4: 385-399. doi:10.1162/tacl_a_00106 – vía ACLWEB.
Altszyler, E.; Ribeiro, S.; Sigman, M.; Fernández Slezak, D. (2017). «The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text». Consciousness and Cognition 56: 178-187. PMID 28943127. S2CID 195347873. arXiv:1610.01520. doi:10.1016/j.concog.2017.09.004.

github.com

«Doc2vec for IMDB sentiment analysis». GitHub. Consultado el 18 de febrero de 2016.

groups.google.com

«Parameter (hs & negative)». Google Groups. Consultado el 13 de junio de 2016.

harvard.edu

adsabs.harvard.edu

Mikolov, Tomas; Sutskever, Ilya; Chen, Kai; Corrado, Greg S.; Dean, Jeff (2013). Distributed representations of words and phrases and their compositionality. Advances in Neural Information Processing Systems. Bibcode:2013arXiv1310.4546M. arXiv:1310.4546.
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.

medium.com

«Doc2Vec tutorial using Gensim». Consultado el 2 de agosto de 2015.

mit.edu

jmlr.csail.mit.edu

«Visualizing Data using t-SNE». Journal of Machine Learning Research, 2008. Vol. 9, pg. 2595. Consultado el 18 de marzo de 2017.

nih.gov

ncbi.nlm.nih.gov

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.
Banerjee, Imon; Chen, Matthew C.; Lungren, Matthew P.; Rubin, Daniel L. (2018). «Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort». Journal of Biomedical Informatics 77: 11-20. PMC 5771955. PMID 29175548. doi:10.1016/j.jbi.2017.11.012.
Altszyler, E.; Ribeiro, S.; Sigman, M.; Fernández Slezak, D. (2017). «The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text». Consciousness and Cognition 56: 178-187. PMID 28943127. S2CID 195347873. arXiv:1610.01520. doi:10.1016/j.concog.2017.09.004.

radimrehurek.com

«Gensim - Deep learning with word2vec». Consultado el 10 de junio de 2016.

semanticscholar.org

api.semanticscholar.org

Altszyler, E.; Ribeiro, S.; Sigman, M.; Fernández Slezak, D. (2017). «The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text». Consciousness and Cognition 56: 178-187. PMID 28943127. S2CID 195347873. arXiv:1610.01520. doi:10.1016/j.concog.2017.09.004.

towardsdatascience.com

Doshi, Sanket (17 de marzo de 2019). «Skip-Gram: NLP context words prediction algorithm». Medium (en inglés). Consultado el 16 de abril de 2024.

web.archive.org

«Doc2Vec and Paragraph Vectors for Classification». Archivado desde el original el 31 de diciembre de 2015. Consultado el 13 de enero de 2016.