Cross-language information retrieval (CLIR) is a subfield of information retrieval dealing with retrieving information written in a language different from the language of the user's query. The term "cross-language information retrieval" has many synonyms, of which the following are perhaps the most frequent: cross-lingual information retrieval, translingual information retrieval, multilingual information retrieval. The term "multilingual information retrieval" refers more generally both to technology for retrieval of multilingual collections and to technology which has been moved to handle material in one language to another. The term Multilingual Information Retrieval (MLIR) involves the study of systems that accept queries for information in various languages and return objects (text, a
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| - Hizkuntzarteko informazio-berreskurapen (eu)
- Cross-language information retrieval (en)
- 跨語檢索 (zh)
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| - 跨語檢索，或稱「跨語資訊檢索」(Cross-Language Information Retrieval，CLIR)，其定義採用 Oard, D. W.在1997年發表的文章《Cross-Language Information Retrieval Defined》。跨語檢索意指使用者使用某種自然語言的檢索由另一種語言表達的文件。 舉例來說，使用者使用（自己熟悉的）中文產生一組檢索詞彙進行檢索，而其檢索結果皆以（使用者完全不懂或不熟悉）的日文，所撰寫的文件。 (zh)
- Cross-language information retrieval (CLIR) is a subfield of information retrieval dealing with retrieving information written in a language different from the language of the user's query. The term "cross-language information retrieval" has many synonyms, of which the following are perhaps the most frequent: cross-lingual information retrieval, translingual information retrieval, multilingual information retrieval. The term "multilingual information retrieval" refers more generally both to technology for retrieval of multilingual collections and to technology which has been moved to handle material in one language to another. The term Multilingual Information Retrieval (MLIR) involves the study of systems that accept queries for information in various languages and return objects (text, a (en)
- Hizkuntzarteko informazio-berreskurapena (ingelesez, Cross-language information retrieval (CLIR)) informazioaren berreskurapenaren atal bat da, erabiltzailearen kontsultaren hizkuntzaz ez dauden dokumentuak eskuratzen dituena. Adibidez, erabiltzaile batek ingelesezko kontsulta eginez, frantsesezko dokumentuak eskuratu ditzake. Sistema hauen arkitekturan funtsezko urratsak hiru dira:
* Galderaren itzulpena
* Informazioaren berreskurapeneko sistemak hainbat hizkuntzatarako (IR).
* Dokumentuen itzulpena Euskara ere lantzen duen Dokusare sistema garatu du Elhuyarrek. (eu)
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| - Cross-language information retrieval (CLIR) is a subfield of information retrieval dealing with retrieving information written in a language different from the language of the user's query. The term "cross-language information retrieval" has many synonyms, of which the following are perhaps the most frequent: cross-lingual information retrieval, translingual information retrieval, multilingual information retrieval. The term "multilingual information retrieval" refers more generally both to technology for retrieval of multilingual collections and to technology which has been moved to handle material in one language to another. The term Multilingual Information Retrieval (MLIR) involves the study of systems that accept queries for information in various languages and return objects (text, and other media) of various languages, translated into the user's language. Cross-language information retrieval refers more specifically to the use case where users formulate their information need in one language and the system retrieves relevant documents in another. To do so, most CLIR systems use various translation techniques. CLIR techniques can be classified into different categories based on different translation resources:
* Dictionary-based CLIR techniques
* Parallel corpora based CLIR techniques
* Comparable corpora based CLIR techniques
* Machine translator based CLIR techniques CLIR systems have improved so much that the most accurate multi-lingual and cross-lingual systems today are nearly as effective as monolingual systems. Other related information access tasks, such as media monitoring, information filtering and routing, sentiment analysis, and information extraction require more sophisticated models and typically more processing and analysis of the information items of interest. Much of that processing needs to be aware of the specifics of the target languages it is deployed in. Mostly, the various mechanisms of variation in human language pose coverage challenges for information retrieval systems: texts in a collection may treat a topic of interest but use terms or expressions which do not match the expression of information need given by the user. This can be true even in a mono-lingual case, but this is especially true in cross-lingual information retrieval, where users may know the target language only to some extent. The benefits of CLIR technology for users with poor to moderate competence in the target language has been found to be greater than for those who are fluent. Specific technologies in place for CLIR services include morphological analysis to handle inflection, decompounding or compound splitting to handle compound terms, and translations mechanisms to translate a query from one language to another. The first workshop on CLIR was held in Zürich during the SIGIR-96 conference. Workshops have been held yearly since 2000 at the meetings of the Cross Language Evaluation Forum (CLEF). Researchers also convene at the annual Text Retrieval Conference (TREC) to discuss their findings regarding different systems and methods of information retrieval, and the conference has served as a point of reference for the CLIR subfield. Google Search had a cross-language search feature that was removed in 2013. (en)
- Hizkuntzarteko informazio-berreskurapena (ingelesez, Cross-language information retrieval (CLIR)) informazioaren berreskurapenaren atal bat da, erabiltzailearen kontsultaren hizkuntzaz ez dauden dokumentuak eskuratzen dituena. Adibidez, erabiltzaile batek ingelesezko kontsulta eginez, frantsesezko dokumentuak eskuratu ditzake. Hizkuntza ingeniaritza funtsezkoa da: dokumentuen hizkuntza-errekonozitzaileak, hiztegi eleanitzak eta itzulpen-sistemak funtsezko elementuak izaten baitira. Orokorrean galderen itzulpena da gehien erabiltzen den eredua (dena den testuingurua txikia izan ohi denez zaila da ondo itzultzea), baina dokumentuen itzulpena edo dokumentuen errepresentazio neutroa (Wordnet erabiliz adibidez) izan daitezke beste aukera batzuk (abiadurari begira motelak dira baina azken biak). Itzulpenaren kalitatea handitu ahala doitasuna handituko da estalduraren galerarik gabe. Kalitate txarreko muturrean hitzez hitzezko itzulpena egitea legoke hiztegietan kontsulta eginda, beste muturrean galdera osoa itzultzea itzulpen automatikoko sistemak aplikatuz, eta tartean itzulpen partzialak egitearen aukera. Sistema hauen arkitekturan funtsezko urratsak hiru dira:
* Galderaren itzulpena
* Informazioaren berreskurapeneko sistemak hainbat hizkuntzatarako (IR).
* Dokumentuen itzulpena Azken urratsa hautazkoa izan daiteke, sistema batzuek aurkitutako dokumentuak jatorrizko hizkuntzan aurkezten dizkioteerabiltzaileari. Hainbat teknika garatu izan dira beste hizkuntza batean dauden dokumentu erlazionatuak bilatzeko: dokumentuen sailkapen semantikoa, dokumentuen arteko antzekotasun semantikoa neurtzea, entitate edo terminoetan oinarritutako dokumentu multzokatzea (clustering)... Euskara ere lantzen duen Dokusare sistema garatu du Elhuyarrek. Honen inguruko lehen tailerra Zurichen burutu zen, SIGIR-96 izeneko konferentzian. Bertako aurkezpenak Cross-Language Information Retrieval (Grefenstette, ed; Kluwer, 1998) ISBN 0-7923-8122-X liburuan daude. Hauek urtero burutu ziren 2000. urtera arte, (CLEF) barnean. (eu)
- 跨語檢索，或稱「跨語資訊檢索」(Cross-Language Information Retrieval，CLIR)，其定義採用 Oard, D. W.在1997年發表的文章《Cross-Language Information Retrieval Defined》。跨語檢索意指使用者使用某種自然語言的檢索由另一種語言表達的文件。 舉例來說，使用者使用（自己熟悉的）中文產生一組檢索詞彙進行檢索，而其檢索結果皆以（使用者完全不懂或不熟悉）的日文，所撰寫的文件。 (zh)
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