{"title":"跨语言文档相似度","authors":"A. Muhic, Jan Rupnik, P. Skraba","doi":"10.2498/iti.2012.0467","DOIUrl":null,"url":null,"abstract":"In this paper we investigated how to compute similarities between documents written in different languages based on a weekly aligned multi-lingual collection of documents. Computing the cross-lingual similarities is based on an aligned set of basis vectors obtained by either latent semantic indexing or the k-means algorithm on an aligned multi-lingual corpus. We evaluated the methods on two data sets: Wikipedia and European Parliament Proceedings Parallel Corpus.","PeriodicalId":135105,"journal":{"name":"Proceedings of the ITI 2012 34th International Conference on Information Technology Interfaces","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Cross-lingual document similarity\",\"authors\":\"A. Muhic, Jan Rupnik, P. Skraba\",\"doi\":\"10.2498/iti.2012.0467\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we investigated how to compute similarities between documents written in different languages based on a weekly aligned multi-lingual collection of documents. Computing the cross-lingual similarities is based on an aligned set of basis vectors obtained by either latent semantic indexing or the k-means algorithm on an aligned multi-lingual corpus. We evaluated the methods on two data sets: Wikipedia and European Parliament Proceedings Parallel Corpus.\",\"PeriodicalId\":135105,\"journal\":{\"name\":\"Proceedings of the ITI 2012 34th International Conference on Information Technology Interfaces\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ITI 2012 34th International Conference on Information Technology Interfaces\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2498/iti.2012.0467\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ITI 2012 34th International Conference on Information Technology Interfaces","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2498/iti.2012.0467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we investigated how to compute similarities between documents written in different languages based on a weekly aligned multi-lingual collection of documents. Computing the cross-lingual similarities is based on an aligned set of basis vectors obtained by either latent semantic indexing or the k-means algorithm on an aligned multi-lingual corpus. We evaluated the methods on two data sets: Wikipedia and European Parliament Proceedings Parallel Corpus.
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