A web-aided query translation expansion method in Cross-Language Information Retrieval (CLIR) is presented in this study. The method is applied to English/Chinese language pair, in which queries are expressed in English and the documents returned are in Chinese. Among the three main categories of CLIR methods of machine translation (MT), dictionary translation using a machine-readable dictionary (MRD), and parallel corpus, our method is based on the second one. MRD-based method is easy to implement. However, it faces the resource limitation problem, i.e., the dictionary is often incomplete leading to poor translation and hence undesirable results. By combining MRD and web-aided query translation expansion technique, good retrieval performance can be achieved. The performance gain is largely due to the successful translation extraction of relevant words of a query term from online texts. A new Chinese word discovery algorithm, which extracts words from continuous Chinese characters was designed and used for this purpose. The extracted relevant words do not only include the precise translation of a query term, but also those words that are relevant to that term in the source language. / Jin Honglan. / "October 2005." / Adviser: Kam Fai Wong. / Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3899. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (p. 115-121). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.

Victor H. Yngve. / Cover title. "Reprint from Proceedings of the American Philosophical Society, vol.104, no.5." / Includes bibliographical references.

University of Macau / Faculty of Social Sciences and Humanities / Department of English

Thesis (MSc)--University of Stellenbosch, 2007. / ENGLISH ABSTRACT: Machine translation, especially machine translation for sign languages, remains an active research area. Sign language machine translation presents unique challenges to the whole machine translation process. In this thesis a prototype machine translation system is presented. This system is designed to translate English text into a gloss based representation of South African Sign Language (SASL). In order to perform the machine translation, a transfer based approach was taken. English text is parsed into an intermediate representation. Translation rules are then applied to this intermediate representation to transform it into an equivalent intermediate representation for the SASL glosses. For both these intermediate representations, a tree adjoining grammar (TAG) formalism is used. As part of the prototype machine translation system, a TAG parser was implemented. The translation rules used by the system were derived from a SASL phrase book. This phrase book was also used to create a small gloss based SASL TAG grammar. Lastly, some additional tools, for the editing of TAG trees, were also added to the prototype system. / AFRIKAANSE OPSOMMING: Masjienvertaling, veral masjienvertaling vir gebaretale, bly ’n aktiewe navorsingsgebied. Masjienvertaling vir gebaretale bied unieke uitdagings tot die hele masjienvertalingproses. In hierdie tesis bied ons ’n prototipe masjienvertalingstelsel aan. Hierdie stelsel is ontwerp om Engelse teks te vertaal na ’n glos gebaseerde voorstelling van Suid-Afrikaanse Gebaretaal (SAG). Ons vertalingstelsel maak gebruik van ’n oorplasingsbenadering tot masjienvertaling. Engelse teks word ontleed na ’n intermediˆere vorm. Vertalingre¨els word toegepas op hierdie intermediˆere vorm om dit te transformeer na ’n ekwivalente intermediˆere vorm vir die SAG glosse. Vir beide hierdie intermediˆere vorms word boomkoppelingsgrammatikas (BKGs) gebruik. As deel van die prototipe masjienvertalingstelsel, is ’n BKG sintaksontleder ge¨ımplementeer. Die vertalingre¨els wat gebruik word deur die stelsel, is afgelei vanaf ’n SAG fraseboek. Hierdie fraseboek was ook gebruik om ’n klein BKG vir SAG glosse te ontwikkel. Laastens was addisionele nutsfasiliteite, vir die redigering van BKG bome, ontwikkel.

Li Kar Wing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 88-96). / Abstracts in English and Chinese. / ABSTRACT --- p.i / ACKNOWLEDGEMENTS --- p.v / LIST OF TABLES --- p.viii / LIST OF FIGURES --- p.ix / CHAPTERS / Chapter 1. --- INTRODUCTION --- p.1 / Chapter 1.1 --- Application of corpus-based techniques --- p.2 / Chapter 1.1.1 --- Machine Translation (MT) --- p.2 / Chapter 1.1.1.1 --- Linguistic --- p.3 / Chapter 1.1.1.2 --- Statistical --- p.4 / Chapter 1.1.1.3 --- Lexicon construction --- p.4 / Chapter 1.1.2 --- Cross-lingual Information Retrieval (CLIR) --- p.6 / Chapter 1.1.2.1 --- Controlled vocabulary --- p.6 / Chapter 1.1.2.2 --- Free text --- p.7 / Chapter 1.1.2.3 --- Application corpus-based approach in CLIR --- p.9 / Chapter 1.2 --- Overview of linguistic resources --- p.10 / Chapter 1.3 --- Written language corpora --- p.12 / Chapter 1.3.1 --- Types of corpora --- p.13 / Chapter 1.3.2 --- Limitation of comparable corpora --- p.16 / Chapter 1.4 --- Outline of the dissertation --- p.17 / Chapter 2. --- LITERATURE REVIEW --- p.19 / Chapter 2.1 --- Research in automatic corpus construction --- p.20 / Chapter 2.2 --- Research in translation alignment --- p.25 / Chapter 2.2.1 --- Sentence alignment --- p.27 / Chapter 2.2.2 --- Word alignment --- p.28 / Chapter 2.3 --- Research in alignment of sequences --- p.33 / Chapter 3. --- ALIGNMENT AT WORD LEVEL AND CHARACTER LEVEL --- p.35 / Chapter 3.1 --- Title alignment --- p.35 / Chapter 3.1.1 --- Lexical features --- p.37 / Chapter 3.1.2 --- Grammatical features --- p.40 / Chapter 3.1.3 --- The English/Chinese alignment model --- p.41 / Chapter 3.2 --- Alignment at word level and character level --- p.42 / Chapter 3.2.1 --- Alignment at word level --- p.42 / Chapter 3.2.2 --- Alignment at character level: Longest matching --- p.44 / Chapter 3.2.3 --- Longest common subsequence(LCS) --- p.46 / Chapter 3.2.4 --- Applying LCS in the English/Chinese alignment model --- p.48 / Chapter 3.3 --- Reduce overlapping ambiguity --- p.52 / Chapter 3.3.1 --- Edit distance --- p.52 / Chapter 3.3.2 --- Overlapping in the algorithm model --- p.54 / Chapter 4. --- ALIGNMENT AT TITLE LEVEL --- p.59 / Chapter 4.1 --- Review of score functions --- p.59 / Chapter 4.2 --- The Score function --- p.60 / Chapter 4.2.1 --- (C matches E) and (E matches C) --- p.60 / Chapter 4.2.2 --- Length similarity --- p.63 / Chapter 5. --- EXPERIMENTAL RESULTS --- p.69 / Chapter 5.1 --- Hong Kong government press release articles --- p.69 / Chapter 5.2 --- Hang Seng Bank economic monthly reports --- p.76 / Chapter 5.3 --- Hang Seng Bank press release articles --- p.78 / Chapter 5.4 --- Hang Seng Bank speech articles --- p.81 / Chapter 5.5 --- Quality of the collections and future work --- p.84 / Chapter 6. --- CONCLUSION --- p.87 / Bibliography