Translingual alteration of conceptual information in medical translation

He, Shizhu

doi:10.1002/1097-4571(2000)9999:9999<::aid-asi1006>3.3.co;2-r

Cited by 4 publications

(6 citation statements)

References 12 publications

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“…To construct a parallel corpus, Resnik (1999) used statistical language identification method which was based on character n‐grams to determine the language. According to He (2000), the titles of documents present “micro‐summaries of texts” that contain “the most important focal information in the whole representation” and as “the most concise statement of the content of a document.” In other words, titles function as the condensed summaries of the information and content of the articles. To take the advantage of importance of titles, we use English and Chinese titles as the condensed representation of the English and Chinese documents to construct the bilingual parallel corpus automatically.…”

Section: Problems In Translation Alignmentmentioning

confidence: 99%

“…A lexical item (word) in a title may be a concept in one language (Larson, 1998), where concept is a recognizable unit of meaning in any given language (He, 2000). For a given language, a concept may not only be represented by a word or words, but may also be represented by a morpheme, by an idiomatic expression, by tone, or by word order (He, 2000). A concept represented by a word in one language may be translated into a word, two words, a phrase, or even a sentence in another language.…”

Section: Problems In Translation Alignmentmentioning

confidence: 99%

“…Therefore, conceptual alternation may occur in translation. Nida (He, 2000) explains that conceptual alteration has three major explanations: 1) no two languages were completely isomorphic, 2) different languages might have different domain vocabulary; and 3) some languages were more rhetorical than other languages.…”

Section: Problems In Translation Alignmentmentioning

confidence: 99%

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Automatic construction of English/Chinese parallel corpora

Yang

2003

J. Am. Soc. Inf. Sci.

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As the demand for global information increases significantly, multilingual corpora has become a valuable linguistic resource for applications to cross-lingual information retrieval and natural language processing. In order to cross the boundaries that exist between different languages, dictionaries are the most typical tools. However, the general-purpose dictionary is less sensitive in both genre and domain. It is also impractical to manually construct tailored bilingual dictionaries or sophisticated multilingual thesauri for large applications. Corpusbased approaches, which do not have the limitation of dictionaries, provide a statistical translation model with which to cross the language boundary. There are many domain-specific parallel or comparable corpora that are employed in machine translation and cross-lingual information retrieval. Most of these are corpora between Indo-European languages, such as English/French and English/Spanish. The Asian/Indo-European corpus, especially English/Chinese corpus, is relatively sparse. The objective of the present research is to construct English/ Chinese parallel corpus automatically from the World Wide Web. In this paper, an alignment method is presented which is based on dynamic programming to identify the one-to-one Chinese and English title pairs. The method includes alignment at title level, word level and character level. The longest common subsequence (LCS) is applied to find the most reliable Chinese translation of an English word. As one word for a language may translate into two or more words repetitively in another language, the edit operation, deletion, is used to resolve redundancy. A score function is then proposed to determine the optimal title pairs. Experiments have been conducted to investigate the performance of the proposed method using the daily press release articles by the Hong Kong SAR government as the test bed. The precision of the result is 0.998 while the recall is 0.806.

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Section: Problems In Translation Alignmentmentioning

confidence: 99%

Section: Problems In Translation Alignmentmentioning

confidence: 99%

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Automatic construction of English/Chinese parallel corpora

Yang

2003

J. Am. Soc. Inf. Sci.

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“…Important terms (or concept descriptors) are first extracted from the parallel or comparable corpus automatically using the English term extraction and Chinese term extraction modules. To be more precise, a concept is a recognizable unit of meaning in any given language (He, 2000). A term is a word or expression that has a precise meaning in peculiar to a subject.…”

Section: Automatic Generation Of English/chinese Thesaurusmentioning

confidence: 99%

Automatic generation of English/Chinese thesaurus based on a parallel corpus in laws

Yang

Luk

2003

J. Am. Soc. Inf. Sci.

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The information available in languages other than English in the World Wide Web is increasing significantly. According to a report from Computer Economics in 1999, 54% of Internet users are English speakers (“English Will Dominate Web for Only Three More Years,” Computer Economics, July 9, 1999, http://www.computereconomics.com/new4/pr/pr990610.html). However, it is predicted that there will be only 60% increase in Internet users among English speakers verses a 150% growth among non‐English speakers for the next five years. By 2005, 57% of Internet users will be non‐English speakers. A report by CNN.com in 2000 showed that the number of Internet users in China had been increased from 8.9 million to 16.9 million from January to June in 2000 (“Report: China Internet users double to 17 million,” CNN.com, July, 2000, http://cnn.org/2000/TECH/computing/07/27/china.internet.reut/index.html). According to Nielsen/NetRatings, there was a dramatic leap from 22.5 millions to 56.6 millions Internet users from 2001 to 2002. China had become the second largest global at‐home Internet population in 2002 (US's Internet population was 166 millions) (Robyn Greenspan, “China Pulls Ahead of Japan,” Internet.com, April 22, 2002, http://cyberatlas.internet.com/big_picture/geographics/article/0,,5911_1013841,00.html). All of the evidences reveal the importance of cross‐lingual research to satisfy the needs in the near future. Digital library research has been focusing in structural and semantic interoperability in the past. Searching and retrieving objects across variations in protocols, formats and disciplines are widely explored (Schatz, B., & Chen, H. (1999). Digital libraries: technological advances and social impacts. IEEE Computer, Special Issue on Digital Libraries, February, 32(2), 45–50.; Chen, H., Yen, J., & Yang, C.C. (1999). International activities: development of Asian digital libraries. IEEE Computer, Special Issue on Digital Libraries, 32(2), 48–49.). However, research in crossing language boundaries, especially across European languages and Oriental languages, is still in the initial stage. In this proposal, we put our focus on cross‐lingual semantic interoperability by developing automatic generation of a cross‐lingual thesaurus based on English/Chinese parallel corpus. When the searchers encounter retrieval problems, professional librarians usually consult the thesaurus to identify other relevant vocabularies. In the problem of searching across language boundaries, a cross‐lingual thesaurus, which is generated by co‐occurrence analysis and Hopfield network, can be used to generate additional semantically relevant terms that cannot be obtained from dictionary. In particular, the automatically generated cross‐lingual thesaurus is able to capture the unknown words that do not exist in a dictionary, such as names of persons, organizations, and events. Due to Hong Kong's unique history background, both English and Chinese are used as official languages in all legal documents. Therefore, English/Chinese cross‐lin...

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“…Further evidence for this is provided by studies of the problems of dealing with medical concepts when medical information is translated from one (natural) language to another; see, for example, He [89].…”

Section: World 3; the Health-care Knowledge Basementioning

confidence: 99%