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dc.contributor.authorGraham, Yvetteen
dc.date.accessioned2021-03-29T09:25:10Z
dc.date.available2021-03-29T09:25:10Z
dc.date.issued2020en
dc.date.submitted2020en
dc.identifier.citationChenyang Lyu, Jennifer Foster, Yvette Graham, Improving Document-level Sentiment Analysis with User and Product Context, Proceedings of the 28th International Conference on Computational Linguistics (COLING), 28th International Conference on Computational Linguistics (COLING), Virtual, Association for Computational Linguistics, 2020, 6724 - 6729en
dc.identifier.otherYen
dc.identifier.urihttp://hdl.handle.net/2262/95919
dc.descriptionPUBLISHEDen
dc.descriptionVirtualen
dc.description.abstractPast work that improves document-level sentiment analysis by encoding user and product information has been limited to considering only the text of the current review. We investigate incorporating additional review text available at the time of sentiment prediction that may prove meaningful for guiding prediction. Firstly, we incorporate all available historical review text belonging to the author of the review in question. Secondly, we investigate the inclusion of historical reviews associated with the current product (written by other users). We achieve this by explicitly storing representations of reviews written by the same user and about the same product and force the model to memorize all reviews for one particular user and product. Additionally, we drop the hierarchical architecture used in previous work to enable words in the text to directly attend to each other. Experiment results on IMDB, Yelp 2013 and Yelp 2014 datasets show improvement to state-of-the-art of more than 2 percentage points in the best case.en
dc.format.extent6724en
dc.format.extent6729en
dc.language.isoenen
dc.publisherAssociation for Computational Linguisticsen
dc.rightsYen
dc.titleImproving Document-level Sentiment Analysis with User and Product Contexten
dc.title.alternativeProceedings of the 28th International Conference on Computational Linguistics (COLING)en
dc.title.alternative28th International Conference on Computational Linguistics (COLING)en
dc.typeConference Paperen
dc.contributor.sponsorSFI stipenden
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/ygrahamen
dc.identifier.rssinternalid226537en
dc.identifier.doihttp://dx.doi.org/10.18653/v1/2020.coling-main.590en
dc.rights.ecaccessrightsopenAccess
dc.contributor.sponsorGrantNumber18/CRT/6183en
dc.subject.TCDThemeDigital Engagementen
dc.subject.TCDThemeInclusive Societyen
dc.subject.TCDTagARTIFICIAL INTELLIGENCEen
dc.subject.TCDTagNatural Language Processingen
dc.subject.TCDTagsentiment analysisen
dc.identifier.orcid_id0000-0001-6741-4855en
dc.subject.darat_thematicCommunicationen
dc.subject.darat_thematicGlobalizationen
dc.status.accessibleNen


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