{"type":"ScholarlyArticle","title":"Distributional Correspondence Indexing for Cross-Lingual and Cross-Domain Sentiment Classification (Extended Abstract)","authors":[{"name":"Alejandro Moreo Fernández","slug":"alejandro-moreo-fernandez","given":"Alejandro Moreo","family":"Fernández","affiliation":"Istituto di Scienza e Tecnologie dell'Informazione , Consiglio Nazionale delle Ricerche"},{"name":"Andrea Esuli","slug":"andrea-esuli","given":"Andrea","family":"Esuli","affiliation":"Istituto di Scienza e Tecnologie dell'Informazione , Consiglio Nazionale delle Ricerche"},{"name":"Fabrizio Sebastiani","slug":"fabrizio-sebastiani","given":"Fabrizio","family":"Sebastiani","affiliation":"Istituto di Scienza e Tecnologie dell'Informazione , Consiglio Nazionale delle Ricerche"}],"abstract":"Domain Adaptation (DA) techniques aim at enabling machine learning methods learn effective classifiers for a “target” domain when the only available training data belongs to a different “source” domain. In this extended abstract, we briefly describe our new DA method called Distributional Correspondence Indexing (DCI) for sentiment classification. DCI derives term representations in a vector space common to both domains where each dimension reflects its distributional correspondence to a pivot, i.e., to a highly predictive term that behaves similarly across domains. The experiments we have conducted show that DCI obtains better performance than current state-of-the-art techniques for cross-lingual and cross-domain sentiment classification.","doi":"10.24963/ijcai.2018/802","url":"https://ijcai.org/proceedings/2018/802","pdf":"https://ijcai.org/proceedings/2018/0802.pdf","markdown":"https://ijcai.org/proceedings/2018/802.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/802","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Journal track","track":"Journal track","number":802,"pages":{"first":5647,"last":5651},"keywords":["Machine Learning: Transfer, Adaptation, Multi-task Learning","Natural Language Processing: Text Classification","Natural Language Processing: Sentiment Analysis and Text Mining"],"videos":[],"references":[{"position":1,"raw":"[Blei et al., 2003] David M. 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