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Overview of Cross-Language Information Retrieval (CLIR) and Its Importance in Multilingual Searches

This overview discusses Cross-Language Information Retrieval (CLIR) and its relevance to searching multilingual document collections. CLIR facilitates querying in multiple languages and allows access to documents that may not be in the user's preferred language. The distinction between CLIR and Multilingual Information Retrieval (MLIR) is clarified, emphasizing the need for CLIR systems to access diverse collections and assist non-fluent language users. Various approaches, such as machine translation and dictionary-based methods, are explored, highlighting the challenges and significance of CLIR in modern information retrieval.

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Overview of Cross-Language Information Retrieval (CLIR) and Its Importance in Multilingual Searches

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  1. Cross-Language IR: An Overview Bernardine Reitmeyer WIRED 12/2/04

  2. What is CLIR? • IR on a monolingual document collection that can be queried in multiple languages • IR on a multilingual document collection, where queries can retrieve documents in multiple languages • IR on multilingual documents (Hull & Grefenstette, 1996)

  3. CLIR vs. MLIR • Cross-language information retrieval refers to the 3 definitions we’ve discussed. • Multilingual information retrieval (MLIR) includes CLIR and IR in systems that use a language other than that of the searcher (query must also be in the other language) • Most people still use MLIR to describe any work in this area • Emphasis here is cross-language

  4. Why do we need CLIR systems? • To search collections containing documents in many languages • To search documents containing text in more than one language • For those who aren’t fluent in a foreign language but can make use of some contents of documents retrieved (images, names, etc.) (Oard & Dorr, 1996)

  5. General Issues With CLIR • Multilingual text access (character sets, etc.) • Differences between languages -stemming, compound words, breaks between words, etc. • Term ambiguity between languages • When to translate (query vs. document)

  6. Basic Approaches to CLIR • Machine Translation/Machine Learning (automatic translation of documents or queries) • Controlled Vocabulary (use of multilingual thesaurus) • Dictionary-Based Approaches (combination of monolingual or bilingual dictionaries – similar to a thesaurus)

  7. Basic Approaches Cont’d… • Latent Semantic Indexing (makes comparisons between semantically related words) • Corpora-Based Approaches (uses existing texts to automatically build information about relationships between terms)

  8. Conclusions • Although CLIR faces many tough issues, it is an important and growing facet of IR. Starting in 2000, it even got its own conference (because it was getting lots of attention at the TREC conferences) called CLEF (Cross-Language Evaluation Forum). • For more information: http://www.ischool.utexas.edu/~pinchy77/clir.doc

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