Academic literature on the topic 'Cross lingual information retrieval'

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Journal articles on the topic "Cross lingual information retrieval"

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Capstick, Joanne, Abdel Kader Diagne, Gregor Erbach, Hans Uszkoreit, Anne Leisenberg, and Manfred Leisenberg. "A system for supporting cross-lingual information retrieval." Information Processing & Management 36, no. 2 (2000): 275–89. http://dx.doi.org/10.1016/s0306-4573(99)00058-8.

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Feng, Kai, Lan Huang, Hao Xu, Kangping Wang, Wei Wei, and Rui Zhang. "Deep Multilabel Multilingual Document Learning for Cross-Lingual Document Retrieval." Entropy 24, no. 7 (2022): 943. http://dx.doi.org/10.3390/e24070943.

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Cross-lingual document retrieval, which aims to take a query in one language to retrieve relevant documents in another, has attracted strong research interest in the last decades. Most studies on this task start with cross-lingual comparisons at the word level and then represent documents via word embeddings, which leads to insufficient structure information. In this work, the cross-lingual comparison at the document level is achieved through the cross-lingual semantic space. Our method, MDL (deep multilabel multilingual document learning), leverages a six-layer fully connected network to proj
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Zuliarso, Eri, Retantyo Wardoyo, Sri Hartati, and Khabib Mustofa. "Indonesian-english cross-lingual legal ontology for information retrieval." International journal of Web & Semantic Technology 6, no. 4 (2015): 01–10. http://dx.doi.org/10.5121/ijwest.2015.6401.

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Gupta, Suneet Kumar, Amit Sinha, and Mradul Jain. "Cross Lingual Information Retrieval With SMT And Query Mining." Advanced Computing: An International Journal 2, no. 5 (2011): 33–39. http://dx.doi.org/10.5121/acij.2011.2504.

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Saad, Farag, and Andreas Nürnberger. "Overview of prior-art cross-lingual information retrieval approaches." World Patent Information 34, no. 4 (2012): 304–14. http://dx.doi.org/10.1016/j.wpi.2012.08.013.

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Sorg, P., and P. Cimiano. "Exploiting Wikipedia for cross-lingual and multilingual information retrieval." Data & Knowledge Engineering 74 (April 2012): 26–45. http://dx.doi.org/10.1016/j.datak.2012.02.003.

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Jena, Gouranga Charan, and Siddharth Swarup Rautaray. "A comprehensive survey on cross-language information retrieval system." Indonesian Journal of Electrical Engineering and Computer Science 14, no. 1 (2019): 127. http://dx.doi.org/10.11591/ijeecs.v14.i1.pp127-134.

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Cross language information retrieval (CLIR) is a retrieval process in which the user fires queries in one language to retrieve information from another (different) language. The diversity of information and language barriers are the serious issues for communication and cultural exchange across the world. To solve such barriers, Cross language information retrieval system, are nowadays in strong demand. CLIR is a subset of Information Retrieval (IR) system. Information Retrieval deals with finding useful information from a large collection of unstructured, structured and semi-structured data to
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Li, Juntao, Chang Liu, Jian Wang, et al. "Cross-Lingual Low-Resource Set-to-Description Retrieval for Global E-Commerce." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (2020): 8212–19. http://dx.doi.org/10.1609/aaai.v34i05.6335.

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With the prosperous of cross-border e-commerce, there is an urgent demand for designing intelligent approaches for assisting e-commerce sellers to offer local products for consumers from all over the world. In this paper, we explore a new task of cross-lingual information retrieval, i.e., cross-lingual set-to-description retrieval in cross-border e-commerce, which involves matching product attribute sets in the source language with persuasive product descriptions in the target language. We manually collect a new and high-quality paired dataset, where each pair contains an unordered product att
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Ghanbari, Elham, and Azadeh Shakery. "Query-dependent learning to rank for cross-lingual information retrieval." Knowledge and Information Systems 59, no. 3 (2018): 711–43. http://dx.doi.org/10.1007/s10115-018-1232-8.

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Lu, Chao, Chengzhi Zhang, and Daqing He. "Comparative analysis of book tags: a cross-lingual perspective." Electronic Library 34, no. 4 (2016): 666–82. http://dx.doi.org/10.1108/el-03-2015-0042.

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Purpose In the era of social media, users all over the world annotate books with social tags to express their preferences and interests. The purpose of this paper is to explore different tagging behaviours by analysing the book tags in different languages. Design/methodology/approach This investigation collected nearly 56,000 tags of 1,200 books from one Chinese and two English online bookmarking systems; it combined content analysis and machine-processing methods to evaluate the similarities and differences between different tagging systems from a cross-lingual perspective. Jaccard’s coeffici
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Dissertations / Theses on the topic "Cross lingual information retrieval"

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Liu, Qing. "A Neural Approach to Cross-Lingual Information Retrieval." Research Showcase @ CMU, 2018. http://repository.cmu.edu/theses/135.

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With the rapid growth of world-wide information accessibility, cross-language information retrieval (CLIR) has become a prominent concern for search engines. Traditional CLIR technologies require special purpose components and need high quality translation knowledge (e.g. machine readable dictionaries, machine translation systems) and careful tuning to achieve high ranking performance. However, with the help of a neural network architecture, it’s possible to solve CLIR problem without extra tuning or special components. This work proposes a bilingual training approach, a neural CLIR solution a
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陸穎剛 and Wing-kong Luk. "Concept space approach for cross-lingual information retrieval." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B30147724.

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Luk, Wing-kong. "Concept space approach for cross-lingual information retrieval /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B2275345X.

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Boynuegri, Akif. "Cross-lingual Information Retrieval On Turkish And English Texts." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12611903/index.pdf.

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In this thesis, cross-lingual information retrieval (CLIR) approaches are comparatively evaluated for Turkish and English texts. As a complementary study, knowledge-based methods for word sense disambiguation (WSD), which is one of the most important parts of the CLIR studies, are compared for Turkish words. Query translation and sense indexing based CLIR approaches are used in this study. In query translation approach, we use automatic and manual word sense disambiguation methods and Google translation service during translation of queries. In sense indexing based approach, documents are inde
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Wang, Xinkai. "Chinese-English cross-lingual information retrieval in biomedicine using ontology-based query expansion." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/chineseenglish-crosslingual-information-retrieval-in-biomedicine-using-ontologybased-query-expansion(1b7443d3-3baf-402b-83bb-f45e78876404).html.

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In this thesis, we propose a new approach to Chinese-English Biomedical cross-lingual information retrieval (CLIR) using query expansion based on the eCMeSH Tree, a Chinese-English ontology extended from the Chinese Medical Subject Headings (CMeSH) Tree. The CMeSH Tree is not designed for information retrieval (IR), since it only includes heading terms and has no term weighting scheme for these terms. Therefore, we design an algorithm, which employs a rule-based parsing technique combined with the C-value term extraction algorithm and a filtering technique based on mutual information, to extra
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Ahmed, Farag [Verfasser], and Andreas [Akademischer Betreuer] Nürnberger. "Meaning refinement to improve cross-lingual information retrieval / Farag Ahmed. Betreuer: Andreas Nürnberger." Magdeburg : Universitätsbibliothek, 2012. http://d-nb.info/1047596040/34.

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Ahmed, Farag Verfasser], and Andreas [Akademischer Betreuer] [Nürnberger. "Meaning refinement to improve cross-lingual information retrieval / Farag Ahmed. Betreuer: Andreas Nürnberger." Magdeburg : Universitätsbibliothek, 2012. http://nbn-resolving.de/urn:nbn:de:gbv:ma9:1-730.

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Tang, Ling-Xiang. "Link discovery for Chinese/English cross-language web information retrieval." Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/58416/1/Ling-Xiang_Tang_Thesis.pdf.

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Nowadays people heavily rely on the Internet for information and knowledge. Wikipedia is an online multilingual encyclopaedia that contains a very large number of detailed articles covering most written languages. It is often considered to be a treasury of human knowledge. It includes extensive hypertext links between documents of the same language for easy navigation. However, the pages in different languages are rarely cross-linked except for direct equivalent pages on the same subject in different languages. This could pose serious difficulties to users seeking information or knowledge f
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Asian, Jelita, and jelitayang@gmail com. "Effective Techniques for Indonesian Text Retrieval." RMIT University. Computer Science and Information Technology, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080110.084651.

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The Web is a vast repository of data, and information on almost any subject can be found with the aid of search engines. Although the Web is international, the majority of research on finding of information has a focus on languages such as English and Chinese. In this thesis, we investigate information retrieval techniques for Indonesian. Although Indonesia is the fourth most populous country in the world, little attention has been given to search of Indonesian documents. Stemming is the process of reducing morphological variants of a word to a common stem form. Previous research has show
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Saad, Motaz. "Fouille de documents et d'opinions multilingue." Thesis, Université de Lorraine, 2015. http://www.theses.fr/2015LORR0003/document.

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L’objectif de cette thèse est d’étudier les sentiments dans les documents comparables. Premièrement, nous avons recueillis des corpus comparables en anglais, français et arabe de Wikipédia et d’Euronews, et nous avons aligné ces corpus au niveau document. Nous avons en plus collecté des documents d’informations des agences de presse locales et étrangères dans les langues anglaise et arabe. Les documents en anglais ont été recueillis du site de la BBC, ceux en arabe du site d’Al-Jazzera. Deuxièmement, nous avons présenté une mesure de similarité cross-linguistique des documents dans le but de r
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Books on the topic "Cross lingual information retrieval"

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Japan) NTCIR Workshop Meeting (7th 2008 Tokyo. NTCIR Workshop 7 Meeting: Proceedings of the 7th NTCIR Workshop Meeting on evaluation of information access technologies : information retrieval, question answering and cross-lingual information access. National Institute of Informatics, 2008.

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Nie, Jian-Yun. Cross-Language Information Retrieval. Springer International Publishing, 2010. http://dx.doi.org/10.1007/978-3-031-02138-1.

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Grefenstette, Gregory, ed. Cross-Language Information Retrieval. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5661-9.

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1956-, Grefenstette Gregory, ed. Cross-language information retrieval. Kluwer Academic Publishers, 1998.

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Peters, C. Multilingual information retrieval. Springer, 2012.

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Padó, Sebastian. Cross-lingual annotation projection models for role-semantic information. Saarland University, 2007.

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Peters, Carol, ed. Cross-Language Information Retrieval and Evaluation. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44645-1.

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Peters, Carol, Martin Braschler, Julio Gonzalo, and Michael Kluck, eds. Advances in Cross-Language Information Retrieval. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/b12018.

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Peters, Carol, Martin Braschler, Julio Gonzalo, and Michael Kluck, eds. Evaluation of Cross-Language Information Retrieval Systems. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45691-0.

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International Federation of Library Associations and Institutions. Working Group on GARE revision., ed. Guidelines for authority records and references. 2nd ed. K.G. Saur, 2001.

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Book chapters on the topic "Cross lingual information retrieval"

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Fluhr, Christian, Dominique Schmit, Philippe Ortet, Faza Elkateb, Karine Gurtner, and Khaled Radwan. "Distributed Cross-Lingual Information Retrieval." In Cross-Language Information Retrieval. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5661-9_4.

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Parton, Kristen, and Jianfeng Gao. "Combining Signals for Cross-Lingual Relevance Feedback." In Information Retrieval Technology. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35341-3_31.

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Lindén, Krister. "Finding Cross-Lingual Spelling Variants." In String Processing and Information Retrieval. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30213-1_21.

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Jan, Ea-Ee, Shih-Hsiang Lin, and Berlin Chen. "Transliteration Retrieval Model for Cross Lingual Information Retrieval." In Information Retrieval Technology. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17187-1_17.

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Rao, T. Pattabhi R. K., and Sobha Lalitha Devi. "Tamil English Cross Lingual Information Retrieval." In Multilingual Information Access in South Asian Languages. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40087-2_26.

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Wang, Peng, and Pete Smith. "Multilingual and cross-lingual information retrieval." In Multilingual Artificial Intelligence. Routledge, 2025. https://doi.org/10.4324/9781003470557-8.

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Yang, Cheng-Zen, Che-Min Chen, and Ing-Xiang Chen. "A Cross-Lingual Framework for Web News Taxonomy Integration." In Information Retrieval Technology. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11880592_21.

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Kwok, Kui-Lam, and Peter Deng. "Chinese Question-Answering: Comparing Monolingual with English-Chinese Cross-Lingual Results." In Information Retrieval Technology. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11880592_19.

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Tang, Ling-Xiang, Andrew Trotman, Shlomo Geva, and Yue Xu. "Cross-Lingual Knowledge Discovery: Chinese-to-English Article Linking in Wikipedia." In Information Retrieval Technology. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35341-3_24.

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Moen, Hans, and Erwin Marsi. "Cross-Lingual Random Indexing for Information Retrieval." In Statistical Language and Speech Processing. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39593-2_15.

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Conference papers on the topic "Cross lingual information retrieval"

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Changala, Ravindra, S. Barathi, R. Subhashini, Joy Christy Lawrance, Anuradha S, and B. Kiran Bala. "Implementing Cross-Lingual Information Retrieval Systems to Enhance Resource Accessibility in English Language Learning." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10725465.

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Li, Huayang, Deng Cai, Zhi Qu, et al. "Cross-lingual Contextualized Phrase Retrieval." In Findings of the Association for Computational Linguistics: EMNLP 2024. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.findings-emnlp.383.

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Palma Gomez, Frank, Ramon Sanabria, Yun-hsuan Sung, Daniel Cer, Siddharth Dalmia, and Gustavo Hernandez Abrego. "Transforming LLMs into Cross-modal and Cross-lingual Retrieval Systems." In Proceedings of the 21st International Conference on Spoken Language Translation (IWSLT 2024). Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.iwslt-1.4.

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Al-Barham, Muhammad, Imad Afyouni, Khalid Almubarak, Ashraf Elnagar, Ayad Turky, and Ibrahim Hashem. "AraCLIP: Cross-Lingual Learning for Effective Arabic Image Retrieval." In Proceedings of The Second Arabic Natural Language Processing Conference. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.arabicnlp-1.9.

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Limkonchotiwat, Peerat, Wuttikorn Ponwitayarat, Lalita Lowphansirikul, et al. "McCrolin: Multi-consistency Cross-lingual Training for Retrieval Question Answering." In Findings of the Association for Computational Linguistics: EMNLP 2024. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.findings-emnlp.157.

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Li, Bryan, Samar Haider, Fiona Luo, Adwait Agashe, and Chris Callison-Burch. "BordIRlines: A Dataset for Evaluating Cross-lingual Retrieval Augmented Generation." In Proceedings of the First Workshop on Advancing Natural Language Processing for Wikipedia. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.wikinlp-1.3.

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Jiang, Zhijie, Zejian Shi, Xinyu Gao, and Yun Xiong. "Enhancing Code Generation Through Retrieval of Cross-Lingual Semantic Graphs." In 2024 31st Asia-Pacific Software Engineering Conference (APSEC). IEEE, 2024. https://doi.org/10.1109/apsec65559.2024.00026.

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Pourmahmoud, Solmaz, and Mehrnoush Shamsfard. "Semantic Cross-lingual Information Retrieval." In 2008 23rd International Symposium on Computer and Information Sciences (ISCIS). IEEE, 2008. http://dx.doi.org/10.1109/iscis.2008.4717868.

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Gore, James, Joseph Polletta, and Behrooz Mansouri. "CrossMath: Towards Cross-lingual Math Information Retrieval." In ICTIR '24: The 2024 ACM SIGIR International Conference on the Theory of Information Retrieval. ACM, 2024. http://dx.doi.org/10.1145/3664190.3672531.

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Xu, Jinxi, and Ralph Weischedel. "Cross-lingual information retrieval using hidden Markov models." In the 2000 Joint SIGDAT conference. Association for Computational Linguistics, 2000. http://dx.doi.org/10.3115/1117794.1117806.

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Reports on the topic "Cross lingual information retrieval"

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Bader, Brett William, Peter Chew, Ahmed Abdelali, and Tamara Gibson Kolda. Cross-language information retrieval using PARAFAC2. Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/908061.

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Demner-Fushman, Dina, and Douglas W. Oard. The Effect of Bilingual Term List Size on Dictionary-Based Cross-Language Information Retrieval. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada447948.

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Demner-Fushman, Dina, and Douglas W. Oard. The Effect of Bilingual Term List Size on Dictionary-Based Cross-Language Information Retrieval. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada452813.

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Dorr, Bonnie J., Dekang Lin, and Gina-Anne Levow. Construction of a Chinese-English Verb Lexicon for Embedded Machine Translation in Cross-Language Information Retrieval. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada459245.

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