Academic literature on the topic 'OOV translation'
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Journal articles on the topic "OOV translation"
Permata, Permata, and Zaenal Abidin. "Statistical Machine Translation Pada Bahasa Lampung Dialek Api Ke Bahasa Indonesia." JURNAL MEDIA INFORMATIKA BUDIDARMA 4, no. 3 (July 20, 2020): 519. http://dx.doi.org/10.30865/mib.v4i3.2116.
Full textAbidin, Zaenal. "Translation of Sentence Lampung-Indonesian Languages with Neural Machine Translation Attention Based Approach." Inovasi Pembangunan : Jurnal Kelitbangan 6, no. 02 (August 1, 2018): 191–206. http://dx.doi.org/10.35450/jip.v6i02.97.
Full textHuang, Chung-Chi, Ho-Ching Yen, Ping-Che Yang, Shih-Ting Huang, and Jason S. Chang. "Using Sublexical Translations to Handle the OOV Problem in Machine Translation." ACM Transactions on Asian Language Information Processing 10, no. 3 (September 2011): 1–20. http://dx.doi.org/10.1145/2002980.2002986.
Full textRaju, B. N. V. Narasimha, M. S. V. S. Bhadri Raju, and K. V. V. Satyanarayana. "Effective preprocessing based neural machine translation for English to Telugu cross-language information retrieval." IAES International Journal of Artificial Intelligence (IJ-AI) 10, no. 2 (June 1, 2021): 306. http://dx.doi.org/10.11591/ijai.v10.i2.pp306-315.
Full textLee, Jangwon, Jungi Lee , Minho Lee , and Gil-Jin Jang. "Named Entity Correction in Neural Machine Translation Using the Attention Alignment Map." Applied Sciences 11, no. 15 (July 29, 2021): 7026. http://dx.doi.org/10.3390/app11157026.
Full textPaul, Saptarshi, and Bipul shyam Purkhyastha. "HANDLING AVIATION OOV WORDS FOR MACHINE TRANSLATION AND CORPUS CREATION." Indian Journal of Computer Science and Engineering 11, no. 5 (October 31, 2020): 471–77. http://dx.doi.org/10.21817/indjcse/2020/v11i5/201105102.
Full textZhang, Ying, Phil Vines, and Justin Zobel. "Chinese OOV translation and post-translation query expansion in chinese--english cross-lingual information retrieval." ACM Transactions on Asian Language Information Processing 4, no. 2 (June 2005): 57–77. http://dx.doi.org/10.1145/1105696.1105697.
Full textAqlan, Fares, Xiaoping Fan, Abdullah Alqwbani, and Akram Al-Mansoub. "Improved Arabic–Chinese Machine Translation with Linguistic Input Features." Future Internet 11, no. 1 (January 19, 2019): 22. http://dx.doi.org/10.3390/fi11010022.
Full textMrinalini, K., T. Nagarajan, and P. Vijayalakshmi. "Pause-Based Phrase Extraction and Effective OOV Handling for Low-Resource Machine Translation Systems." ACM Transactions on Asian and Low-Resource Language Information Processing 18, no. 2 (February 10, 2019): 1–22. http://dx.doi.org/10.1145/3265751.
Full textWang, Longyue, Derek F. Wong, Lidia S. Chao, Yi Lu, and Junwen Xing. "A Systematic Comparison of Data Selection Criteria for SMT Domain Adaptation." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/745485.
Full textDissertations / Theses on the topic "OOV translation"
Zhang, Ying, and ying yzhang@gmail com. "Improved Cross-language Information Retrieval via Disambiguation and Vocabulary Discovery." RMIT University. Computer Science and Information Technology, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20090224.114940.
Full textYen, Ho-ching, and 顏合淨. "Using Sublexical Translations to Handle the OOV Problem in Machine Translation." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/60049015942631967613.
Full text國立清華大學
資訊工程學系
98
本論文提出一個翻譯未知詞的方法，可用於解決機器翻譯中的未知詞問題。產生翻譯的方法，主要是利用未知詞中各組成字的翻譯，使用不同的方式組合以產生該未知詞的翻譯。方法的主要步驟，是從機器翻譯系統原有的詞彙翻譯表中，以未知詞的組成字搭配萬用符號進行查詢，取得各組成字的翻譯，進而由組成字翻譯中組合出該未知詞的翻譯。我們利用雙語與單語資料來篩選和排序本方法產生的未知詞翻譯。本研究的測試方式，是將產生的未知詞翻譯與現有的機器翻譯系統整合，進行中文翻譯至英文的實驗。在評估方面，我們使用BLEU準則來進行評分。實驗結果顯示，當中文句含有較多的未知詞時，本系統提供的未知詞翻譯能改善整體的翻譯品質。本論文的主要貢獻在於，我們的方法利用機器翻譯系統現有的詞彙翻譯表，逐字翻譯未知詞的組成字，並從中組合出未知詞的翻譯，進而幫助解決機器翻譯中的未知詞問題。
Su, Chen-Yu, and 蘇辰豫. "Using N-gram Translation and Wikipedia Translation to Solve OOV Terms in MLIR." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/17253254014178362136.
Full text朝陽科技大學
資訊工程系碩士班
95
The Internet content grows up fast. All kinds of information are on the web. In this era of Information explosion, Information Retrieval can help users to get information they need quickly. Cross-Language Information Retrieval can help users to retrieve documents in another language which is different from the query language. Saving the effort of query translation, users could use Query in their local language to retrieve documents in another language. In this paper, we adopt the dictionary based translation approach to build our CLIR system. We use free online resources to translate the query terms. Free online resources include bilingual dictionary websites, Google online translation services and Wikipedia. We focus on the Wikipedia translation in this research. Each entry of Wikipedia has links to entries in other languages if there are entries describing the same topic in those languages. We use this links to get topic in another language for Wikipedia translation. Since Wikipedia has 253 language versions, theoretically, our CLIR system can cross 253 languages. In the dictionary based CLIR, the performance becomes lower because of the out-of-vocabulary (OOV) terms problem. Most dictionaries do update periodically, but the updating frequency of Wikipedia is much faster. Using Wikipedia translation can help to solve the OOV term problem. We use NTCIR-4 and NTCIR-6 data set for our experiment. For better use the free online translation resource to get best performance, we use N-gram translation, adding source query term, long term translation and Google full translation methods to get high precision. Because it’s suitable to use Wikipedia to translate terms, we use terms for our N-gram unit. The experiment results show that we can achieve state-of-the-art performance on Chinese to Japanese and Japanese to Chinese CLIR.
Mahesh, Kavitha Karimbi. "Augmenting Translation Lexica by Learning Generalised Translation Patterns." Doctoral thesis, 2017. http://hdl.handle.net/10362/21995.
Full text"Phoneme-based statistical transliteration of foreign names for OOV problem." 2004. http://library.cuhk.edu.hk/record=b5896367.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 2004.
Includes bibliographical references (leaves 79-82).
Abstracts in English and Chinese.
Abstract --- p.i
Acknowledgement --- p.iii
Bibliographic Notes --- p.v
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- What is Transliteration? --- p.1
Chapter 1.2 --- Existing Problems --- p.2
Chapter 1.3 --- Objectives --- p.4
Chapter 1.4 --- Outline --- p.4
Chapter 2 --- Background --- p.6
Chapter 2.1 --- Source-channel Model --- p.6
Chapter 2.2 --- Transliteration for English-Chinese --- p.8
Chapter 2.2.1 --- Rule-based Approach --- p.8
Chapter 2.2.2 --- Similarity-based Framework --- p.8
Chapter 2.2.3 --- Direct Semi-Statistical Approach --- p.9
Chapter 2.2.4 --- Source-channel-based Approach --- p.11
Chapter 2.3 --- Chapter Summary --- p.14
Chapter 3 --- Transliteration Baseline --- p.15
Chapter 3.1 --- Transliteration Using IBM SMT --- p.15
Chapter 3.1.1 --- Introduction --- p.15
Chapter 3.1.2 --- GIZA++ for Transliteration Modeling --- p.16
Chapter 3.1.3 --- CMU-Cambridge Toolkits for Language Modeling --- p.21
Chapter 3.1.4 --- Re Write Decoder for Decoding --- p.21
Chapter 3.2 --- Limitations of IBM SMT --- p.22
Chapter 3.3 --- Experiments Using IBM SMT --- p.25
Chapter 3.3.1 --- Data Preparation --- p.25
Chapter 3.3.2 --- Performance Measurement --- p.27
Chapter 3.3.3 --- Experimental Results --- p.27
Chapter 3.4 --- Chapter Summary --- p.28
Chapter 4 --- Direct Transliteration Modeling --- p.29
Chapter 4.1 --- Soundness of the Direct Model一Direct-1 --- p.30
Chapter 4.2 --- Alignment of Phoneme Chunks --- p.31
Chapter 4.3 --- Transliteration Model Training --- p.33
Chapter 4.3.1 --- EM Training for Symbol-mappings --- p.33
Chapter 4.3.2 --- WFST for Phonetic Transition --- p.36
Chapter 4.3.3 --- Issues for Incorrect Syllables --- p.36
Chapter 4.4 --- Language Model Training --- p.36
Chapter 4.5 --- Search Algorithm --- p.39
Chapter 4.6 --- Experimental Results --- p.41
Chapter 4.6.1 --- Experiment I: C.A. Distribution --- p.41
Chapter 4.6.2 --- Experiment II: Top-n Accuracy --- p.41
Chapter 4.6.3 --- Experiment III: Comparisons with the Baseline --- p.43
Chapter 4.6.4 --- Experiment IV： Influence of m Candidates --- p.43
Chapter 4.7 --- Discussions --- p.43
Chapter 4.8 --- Chapter Summary --- p.46
Chapter 5 --- Improving Direct Transliteration --- p.47
Chapter 5.1 --- Improved Direct Model´ؤDirect-2 --- p.47
Chapter 5.1.1 --- Enlightenment from Source-Channel --- p.47
Chapter 5.1.2 --- Using Contextual Features --- p.48
Chapter 5.1.3 --- Estimation Based on MaxEnt --- p.49
Chapter 5.1.4 --- Features for Transliteration --- p.51
Chapter 5.2 --- Direct-2 Model Training --- p.53
Chapter 5.2.1 --- Procedure and Results --- p.53
Chapter 5.2.2 --- Discussions --- p.53
Chapter 5.3 --- Refining the Model Direct-2 --- p.55
Chapter 5.3.1 --- Refinement Solutions --- p.55
Chapter 5.3.2 --- Direct-2R Model Training --- p.56
Chapter 5.4 --- Evaluation --- p.57
Chapter 5.4.1 --- Search Algorithm --- p.57
Chapter 5.4.2 --- Direct Transliteration Models vs. Baseline --- p.59
Chapter 5.4.3 --- Direct-2 vs. Direct-2R --- p.63
Chapter 5.4.4 --- Experiments on Direct-2R --- p.65
Chapter 5.5 --- Chapter Summary --- p.71
Chapter 6 --- Conclusions --- p.72
Chapter 6.1 --- Thesis Summary --- p.72
Chapter 6.2 --- Cross Language Applications --- p.73
Chapter 6.3 --- Future Work and Directions --- p.74
Chapter A --- IPA-ARPABET Symbol Mapping Table --- p.77
Bibliography --- p.82
Opperman, Susan. "Ethical and stylistic issues of translating Bosman's English short stories into Afrikaans." Thesis, 2018. http://hdl.handle.net/10500/24546.
Full textHerman Charles Bosman (1905–1951) remains a popular South African writer, despite the frequent occurrence of the offensive k-word for black people in his writings. Although the discipline of Translation Studies is presently dominated by ethical considerations, there are reasons to believe that ethical issues have been neglected in recent translations of Bosman’s English short stories into Afrikaans. His translators, Griebenow and De Lange, have conformed to a simplistic fidelity-driven perception of ethics, while more attention should have been paid to “sensitive” aspects of the original. The research problem is how this gap that exists in translation practice can be addressed, which in turn raises the question: How would one translate Bosman’s stories in an ethically responsible manner for the twenty-first century? This study not does deal with all of Bosman’s short stories but focuses on the Oom Schalk Lourens ones as these demonstrate the research problem best. Thus, the data consist of existing texts in printed form. The following stories have been selected for comparative analysis: “Makapan’s Caves”, “The Rooinek”, “The Gramophone”, “Mafeking Road”, “Splendours from Ramoutsa”, “Unto Dust”, and “Funeral Earth”. Since excerpts from the original and their corresponding translations are compared, translator style is inevitably included in the discussion. A committed approach, which considers translation as an activist and interventionist cultural activity (Brownlie 2011), forms the analytical framework of this study. The analyses indicate that Griebenow and De Lange have retained the offensive racial epithets of the source texts, rather than toning them down for modern target-text readers. Thus, the translators have been faithful to a dead author, instead of taking the socio-cultural and political context of reception into consideration. From a committed stance, I would strongly recommend that derogatory racial epithets, found in older texts, should be subdued in current translations. Otherwise, it may be better not to translate at all, as Pym (2012) suggests. Owing to translators’ responsibility for the effects of their translations on their readers, and South Africa’s political transformation to a democracy in which all people are deemed equal before the law, the use of racist language, is totally unwarranted.
Herman Charles Bosman (1905–1951) bly ʼn gewilde Suid-Afrikaanse skrywer, ten spyte van die gereelde voorkoms van die neerhalende k-woord vir swart mense in sy werk. Hoewel die dissipline, Vertaalkunde, tans deur etiese vraagstukke oorheers word, is daar rede om te vermoed dat etiese kwessies afgeskeep is in die onlangse vertalings van Bosman se Engelse kortverhale in Afrikaans. Die vertalers, Griebenow en De Lange, vereenselwig etiek met getrouheid aan die skrywer, in plaas daarvan om meer aandag te skenk aan “sensitiewe” aspekte van die oorspronklike. Die navorsingsprobleem is hoe om hierdie gaping in vertaalpraktyk aan te spreek: Hoe behoort Bosman se verhale op ʼn etiese, verantwoordelike wyse vertaal te word vir die een-en-twintigste eeu? Hierdie studie fokus op Bosman se oom Schalk Lourens-verhale wat die navorsingsprobleem die beste illustreer. Die data is derhalwe saamgestel uit bestaande tekste in gedrukte vorm. Die volgende verhale is vir vergelykende ontleding gekies: “Makapan’s Caves”, “The Rooinek”, “The Gramophone”, “Mafeking Road”, “Splendours from Ramoutsa”, “Unto Dust”, en “Funeral Earth”. Aangesien grepe uit die brontekste en die vertalings daarvan vergelyk word, is vertalerstyl noodwendig deel van die bespreking. ʼn Betrokke benadering waarvolgens vertaling as ʼn aktivistiese en intervensionistiese kulturele aktiwiteit beskou word (Brownlie 2011), vorm die ontledingsraamwerk van die studie. Die ontledings dui daarop dat Griebenow en De Lange die rassistiese skeldname van die oorspronklike behou het, in plaas daarvan om dit “sagter” uit te druk vir hedendaagse doeltaallesers. Die vertalers was getrou aan ʼn afgestorwe skrywer, eerder as om die sosiokulturele en -politiese konteks van resepsie in ag te neem. Vanuit ʼn betrokke standpunt sou ek sterk aanbeveel dat neerhalende, rassistiese benamings wat in ouer tekste voorkom, gedemp moet word in hedendaagse vertalings. Anders sou dit beter wees om hoegenaamd nie te vertaal nie, soos Pym (2012) voorstel. Vanweë vertalers se verantwoordelikheid vir die effek van hul vertalings op hul lesers, en Suid-Afrika se politiese transformasie in ʼn demokrasie waar alle mense gelyk geag word voor die wet, is die gebruik van rassistiese taal verregaande.
UHerman Charles Bosman (1905-1951) ngomnye wababhali abaphume izandla baseMzantsi Afrika, nangona iincwadi zakhe zizele ligama elingamkelekanga eliqala ngo-k elibhekiselele kubantu abantsundu. Nangona Izifundo Zoguqulo zikuthathela ingqalelo ukunanzwa kweenqobo ezisesikweni xa kuguqulelwa, kukho izizathu ezibangela ukuba kukholeleke ukuba imiba engeenqobo ezisesikweni iye yatyeshelwa xa bekuguqulelwa kwiAfrikaans amabali amafutshane kaBosman abhalwe ngesiNgesi. UGriebenow noDe Lange abangabaguquli bathande ukulandela uluvo olubonisa intembeko kumbhali, endaweni yokugxila kwimiba “enobuethe-ethe” ekwisicatshulwa sentsusa. Injongo yolu phando kukufumana indlela esinokuvalwa ngayo esi sikhewu kwimisebenzi yoguqulelo, nto leyo ebangela ukuba kubekho imibuzo ethi: Umntu angawaguqula njani amabali amafutshane kaBosman kwinkulungwane yamashumi amabini ananye apho umguquli azithathela ingqalelo iinqobo ezisesikweni. Olu phando aluwahlautyi onke amabali amafutshane kaBosman, koko lugxila kuphela kula ka-Oom Schalk Lourens kuba ingawo ayivelisa kakuhle le ngxaki/njongo yophando. Izicatshulwa ezihlalutywayo zezishicilelweyo kuphela. Amabali akhethelwe ukuthelekiswa nokuhlalutywa ngala: “Makapan’s Caves”, “The Rooinek”, “The Gramophone”, “Mafeking Road”, “Splendours from Ramoutsa”, “Unto Dust”, and “Funeral Earth”. Njengoko kuthelekiswa iziqendwana ezikula mabalana neenguqulelo zawo, isimbo sokubhala sabaguquli siyaqukwa kolu hlalutyo. Isakhelo sohlalutyo esisetyenzisiweyo kolu phando seso sisekelwe kwiingcamango zikaBrownlie (2011) ezihlela uguqulelo njengesenzo senkcubeko sokuphembelela nokungenelela. Uhlalutyo lubonisa ukuba uGriebenow noDe Lange bawagcinile amagama ocalucalulo ngokobuhlanga anyelisayo asetyenziswe kwizicatshulwa zentsusa, endaweni yokuwatshintsha ngelokulungiselela abafundi ekujoliswe kubo beli xesha. Abaguquli ke ngoko baye bathembeka kakhulu kumbhali owaswelekayo endaweni yokuthathela ingqalelo imeko yokwamkelekileyo ngokwezopolitiko nentlalo. Ndiphakamisa ukuba amagama anyelisayo ocalucalulo ngokobuhlanga asetyenziswe kwiimbalo zakudala athonyalaliswe okanye atshintshwe kwiinguqulelo zangoku. Kungenjalo, kungcono kungenziwa nguqulelo kwaphela njengoko ecebisa uPym (2012). Ngenxa yoxanduva olusemagxeni abaguquli ngeziphumo zeenguqulelo zabo kubafundi bazo, nokutshintsha kwemeko yezopolitiko yoMzantsi Afrika itshintshela kwidemokhrasi apho abantu balinganayo ngokomthetho, ukusetyenziswa kolwimi olucalulayo akwamkelekanga.
Linguistics and Modern Languages
D. Litt. et Phil. (Linguistics with specialisation in Translation Studies)
Books on the topic "OOV translation"
(Editor), Maxim Jakubowski, and Franck Spengler (Editor), eds. Ooh La La!: Contemporary French Erotica by Women. Thunder's Mouth Press, 2006.
Find full textFuß, Eric. The OV/VO alternation in early German. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198813545.003.0012.
Full textPublishing, Boss Daddy. WOOF Wa-Oof Woof Woof WOOF Woof WA-OOF Woof { TRANSLATION : Happy Fathers Day DAD } : Funny Fathers Day Gifts from Dog, Cat, Pet : Fathers Day Gifts Card Notebook Keepsake Journal to Share His Life and His Love: Fathers Day Card from Dog Cat Pet to Dad. Independently Published, 2020.
Find full textBook chapters on the topic "OOV translation"
Ge, Yun Dong, Yu Hong, Jian Min Yao, and Qiao Ming Zhu. "Improving Web-Based OOV Translation Mining for Query Translation." In Information Retrieval Technology, 576–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17187-1_54.
Full textQu, Jian, Akira Shimazu, and Minh Le Nguyen. "OOV Term Translation, Context Information and Definition Extraction Based on OOV Term Type Prediction." In Advances in Natural Language Processing, 76–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33983-7_8.
Full textZhao, Yun, Qinen Zhu, Cheng Jin, Yuejie Zhang, Xuanjing Huang, and Tao Zhang. "Chinese-English OOV Term Translation with Web Mining, Multiple Feature Fusion and Supervised Learning." In Lecture Notes in Computer Science, 234–46. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12277-9_21.
Full textShi, Lei. "Mining OOV Translations from Mixed-Language Web Pages for Cross Language Information Retrieval." In Lecture Notes in Computer Science, 471–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12275-0_41.
Full text"Ab Ovo." In Translations from the Flesh, 82. University of Pittsburgh Press, 2013. http://dx.doi.org/10.2307/j.ctv14z1bcn.54.
Full textChoudhary, Abha, and Saroj Nimkarn. "SRY- Negative XX Male and XX Ovo-Testicular DSD in a Set of Identical Adolescent Twins." In CLINICAL/TRANSLATIONAL - Pediatric Endocrinology: Puberty, P3–733—P3–733. The Endocrine Society, 2011. http://dx.doi.org/10.1210/endo-meetings.2011.part4.p13.p3-733.
Full textConference papers on the topic "OOV translation"
Huck, Matthias, Viktor Hangya, and Alexander Fraser. "Better OOV Translation with Bilingual Terminology Mining." In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/p19-1581.
Full textYang Wang, Yue-Jie Zhang, and Tao Zhang. "English-Chinese OOV translation based on PAT Tree." In 2009 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2009. http://dx.doi.org/10.1109/icmlc.2009.5212280.
Full textYu, Haitao, Fuji Ren, Degen Huang, and Lishuang Li. "Designing effective web mining-based techniques for OOV translation." In 2010 International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE). IEEE, 2010. http://dx.doi.org/10.1109/nlpke.2010.5587807.
Full textZhang, Ying, and Phil Vines. "Detection and translation of OOV terms prior to query time." In the 27th annual international conference. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1008992.1009102.
Full textLiu, Lan, Yun-Dong Ge, Zhen-Xiang Yan, and Jian-Min Yao. "A CLIR-oriented OOV translation mining method from bilingual webpages." In 2011 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2011. http://dx.doi.org/10.1109/icmlc.2011.6016958.
Full textAminian, Maryam, Mahmoud Ghoneim, and Mona Diab. "Handling OOV Words in Dialectal Arabic to English Machine Translation." In Proceedings of the EMNLP'2014 Workshop on Language Technology for Closely Related Languages and Language Variants. Stroudsburg, PA, USA: Association for Computational Linguistics, 2014. http://dx.doi.org/10.3115/v1/w14-4213.
Full textZhang, Yue-Jie, Yan-Xia Su, Cheng Jin, and Tao Zhang. "Multi-feature representation for Web-based English-Chinese OOV term translation." In 2011 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2011. http://dx.doi.org/10.1109/icmlc.2011.6016971.
Full textQu, Yun-Qian, Jian-Min Yao, Jun Sun, and Meng Sun. "OOV Translation Mining from Mixed-Language Snippets from a Search Engine." In 2008 9th International Conference for Young Computer Scientists. IEEE, 2008. http://dx.doi.org/10.1109/icycs.2008.91.
Full textLi, Shuang, Meng Sun, Yang Yang, and Jianmin Yao. "Study on Word Alignment for Reordering of Web-mined OOV Translation Candidates." In 11th Joint Conference on Information Sciences. Paris, France: Atlantis Press, 2008. http://dx.doi.org/10.2991/jcis.2008.105.
Full textZhang, Yuejie, Yang Wang, and Xiangyang Xue. "English-Chinese bi-directional OOV translation based on web mining and supervised learning." In the ACL-IJCNLP 2009 Conference Short Papers. Morristown, NJ, USA: Association for Computational Linguistics, 2009. http://dx.doi.org/10.3115/1667583.1667624.
Full text