{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T12:06:23Z","timestamp":1790856383211,"version":"4.1.0"},"reference-count":29,"publisher":"Association for Computing Machinery (ACM)","issue":"1","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Inf. Syst."],"published-print":{"date-parts":[[2007,2]]},"abstract":"<jats:p>We present a method for creating a comparable text corpus from two document collections in different languages. The collections can be very different in origin. In this study, we build a comparable corpus from articles by a Swedish news agency and a U.S. newspaper. The keys with best resolution power were extracted from the documents of one collection, the source collection, by using the relative average term frequency (RATF) value. The keys were translated into the language of the other collection, the target collection, with a dictionary-based query translation program. The translated queries were run against the target collection and an alignment pair was made if the retrieved documents matched given date and similarity score criteria. The resulting comparable collection was used as a similarity thesaurus to translate queries along with a dictionary-based translator. The combined approaches outperformed translation schemes where dictionary-based translation or corpus translation was used alone.<\/jats:p>","DOI":"10.1145\/1198296.1198300","type":"journal-article","created":{"date-parts":[[2007,4,5]],"date-time":"2007-04-05T19:20:08Z","timestamp":1175800808000},"page":"4","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":28,"title":["Creating and exploiting a comparable corpus in cross-language information retrieval"],"prefix":"10.1145","volume":"25","author":[{"given":"Tuomas","family":"Talvensaari","sequence":"first","affiliation":[{"name":"University of Tampere, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jorma","family":"Laurikkala","sequence":"additional","affiliation":[{"name":"University of Tampere, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kalervo","family":"J\u00e4rvelin","sequence":"additional","affiliation":[{"name":"University of Tampere, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martti","family":"Juhola","sequence":"additional","affiliation":[{"name":"University of Tampere, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heikki","family":"Keskustalo","sequence":"additional","affiliation":[{"name":"University of Tampere, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2007,2]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the 5th Text Retrieval Conference (TREC5) Gaithersburg, MD. E. M. Voorhees, D. K. Harman, Eds. National Institute of Standards and Technology","volume":"238","author":"Allan J.","unstructured":"Allan , J. , Callan , J. , Croft , B. , Ballesteros , L. , Broglio , J. , Xu , J. , and Shu , H . 1997. Inquery at TREC 5 . In Proceedings of the 5th Text Retrieval Conference (TREC5) Gaithersburg, MD. E. M. Voorhees, D. K. Harman, Eds. National Institute of Standards and Technology , vol. 500-- 238 , 119--132.]] Allan, J., Callan, J., Croft, B., Ballesteros, L., Broglio, J., Xu, J., and Shu, H. 1997. Inquery at TREC 5. In Proceedings of the 5th Text Retrieval Conference (TREC5) Gaithersburg, MD. E. M. Voorhees, D. K. Harman, Eds. National Institute of Standards and Technology, vol. 500--238, 119--132.]]"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/290941.290958"},{"key":"e_1_2_1_3_1","volume-title":"Proceedings of the 2nd European Conference on Research and Advanced Technology for Digital Libraries","author":"Braschler M.","unstructured":"Braschler , M. and Sch\u00e4uble , P . 1998. Multilingual information retrieval based on document alignment techniques . In Proceedings of the 2nd European Conference on Research and Advanced Technology for Digital Libraries . Heraklion, Greece. C. Nikolaou, C. Stephanidis, Eds. Springer-Verlag, Berlin, Germany, 183--197.]] Braschler, M. and Sch\u00e4uble, P. 1998. Multilingual information retrieval based on document alignment techniques. In Proceedings of the 2nd European Conference on Research and Advanced Technology for Digital Libraries. Heraklion, Greece. C. Nikolaou, C. Stephanidis, Eds. 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Cross-Language Information Retrieval, Kluwer Academic Publishers, 11--22.]]"},{"key":"e_1_2_1_6_1","volume-title":"The 7th Text Retrieval Conference (TREC-7)","volume":"242","author":"Franz M.","unstructured":"Franz , M. , McCarley , J. S. , and Roukos , S . 1999. Ad hoc and multilingual information retrieval at IBM . In The 7th Text Retrieval Conference (TREC-7) . Gaithersburg, MD. E. M. Voorhees, D. K. Harman, Eds. National Institute of Standards and Technology , vol. 500-- 242 , 157--168.]] Franz, M., McCarley, J. S., and Roukos, S. 1999. Ad hoc and multilingual information retrieval at IBM. In The 7th Text Retrieval Conference (TREC-7). Gaithersburg, MD. E. M. Voorhees, D. K. Harman, Eds. 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Lecture Notes in Computer Science , vol. 2857 , Springer, Berlin, Germany, 252--265.]] Keskustalo, H., Pirkola, A., Visala, K., Lepp\u00e4nen, E., and J\u00e4rvelin, K. 2003. Non-adjacent digrams improve matching of cross-lingual spelling variants. In Proceedings of the 10th International Symposium (SPIRE2003). Manaus, Brazil. M. A. Nascimento, E. S. de Moura, A. L. Oliveira, Eds. Lecture Notes in Computer Science, vol. 2857, Springer, Berlin, Germany, 252--265.]]"},{"key":"e_1_2_1_12_1","volume-title":"Two-Level Morphology: A General Computational Model for Word-Form Recognition and Production","author":"Koskenniemi K.","unstructured":"Koskenniemi , K. 1983. Two-Level Morphology: A General Computational Model for Word-Form Recognition and Production . Publications of the Department of General Linguistics, University of Helsinki , No. 11.]] Koskenniemi, K. 1983. Two-Level Morphology: A General Computational Model for Word-Form Recognition and Production. 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