Can domain adaptation be handled as analogies?

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• dc.contributor.author Bel Rafecas, Núria
• dc.contributor.author Pocostales, Joel
• dc.date.accessioned 2019-03-05T09:37:16Z
• dc.date.available 2019-03-05T09:37:16Z
• dc.date.issued 2018
• dc.description Comunicació presentada a: 11th International Conference on Language Resources and Evaluation, celebrada a Miyazaki, Japó, del 7 al 12 de maig del 2018.
• dc.description.abstract Aspect identification in user generated texts by supervised text classification might suffer degradation in performance when changing to other domains than the one used for training. For referring to aspects such as quality, price or customer services the vocabulary might differ and affect performance. In this paper, we present an experiment to validate a method to handle domain shifts when there is no available labeled data to retrain. The system is based on the offset method as used for solving word analogy problems in vector semantic models such as word embedding. Despite of the fact that the offset method indeed found relevant analogues in the new domain for the classifier initial selected features, the classifiers did not deliver the expected results. The analysis showed that a number of words were found as analogues for many different initial features. This phenomenon was already described in the literature as 'default words' or 'hubs'. However, our data showed that it cannot be explained in terms of word frequency or distance to the question word, as suggested.
• dc.description.sponsorship This work was supported by the Spanish TUNER project TIN2015-65308-C5-5-R (MINECO/FEDER, UE).
• dc.format.mimetype application/pdf
• dc.identifier.citation Bel N, Pocostales J. Can domain adaptation be handled as analogies? In: Calzolari N, Choukri K, Cieri C, Declerck T, Goggi S, Hasida K, Isahara H, Maegaard B, Mariani J, Mazo H, Moreno A, Odijk J, Piperidis S, Tokunaga T, editors. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC-2018); 2018 May 7-12; Miyazaki, Japan. France: European Language Resources Association; 2018. p. 2559-65.
• dc.identifier.uri http://hdl.handle.net/10230/36740
• dc.language.iso eng
• dc.publisher ACL (Association for Computational Linguistics)
• dc.relation.ispartof In: Calzolari N, Choukri K, Cieri C, Declerck T, Goggi S, Hasida K, Isahara H, Maegaard B, Mariani J, Mazo H, Moreno A, Odijk J, Piperidis S, Tokunaga T, editors. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC-2018); 2018 May 7-12; Miyazaki, Japan. France: European Language Resources Association; 2018. p. 2559-65.
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TIN2015-65308-C5-5-R
• dc.rights © ACL, Creative Commons Attribution 3.0 License
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://creativecommons.org/licenses/by/3.0/es/
• dc.subject.keyword Aspect identification
• dc.subject.keyword Domain adaptation
• dc.subject.keyword Document classification
• dc.title Can domain adaptation be handled as analogies?
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/publishedVersion