{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:39:47Z","timestamp":1723016387614},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7]]},"abstract":"<jats:p>Domain Adaptation (DA) techniques aim at enabling machine learning methods learn effective classifiers for a \u201ctarget\u201d domain when the only available training data belongs to a different \u201csource\u201d 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.<\/jats:p>","DOI":"10.24963\/ijcai.2018\/802","type":"proceedings-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:49:10Z","timestamp":1530755350000},"page":"5647-5651","source":"Crossref","is-referenced-by-count":0,"title":["Distributional Correspondence Indexing for Cross-Lingual and Cross-Domain Sentiment Classification (Extended Abstract)"],"prefix":"10.24963","author":[{"given":"Alejandro","family":"Moreo Fern\u00e1ndez","sequence":"first","affiliation":[{"name":"Istituto di Scienza e Tecnologie dell\u2019Informazione, Consiglio Nazionale delle Ricerche, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrea","family":"Esuli","sequence":"additional","affiliation":[{"name":"Istituto di Scienza e Tecnologie dell\u2019Informazione, Consiglio Nazionale delle Ricerche, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabrizio","family":"Sebastiani","sequence":"additional","affiliation":[{"name":"Istituto di Scienza e Tecnologie dell\u2019Informazione, Consiglio Nazionale delle Ricerche, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"27","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2018","name":"Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}","start":{"date-parts":[[2018,7,13]]},"theme":"Artificial Intelligence","location":"Stockholm, Sweden","end":{"date-parts":[[2018,7,19]]}},"container-title":["Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:56:11Z","timestamp":1530755771000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2018\/802"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2018\/802","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}