現代的電子文件的量已經巨大地增長，網路科技使用戶獨立地分享信息和知識。語言用來寫文件也有很多種。這種現象引導我們發會放法能精確地檢索文件和以能力解決语言障隘。
本這次研究， 我們發會相似度放法用來從論文和學術論文系統檢索雙語科學文件。我們計算雙語文件相似度(漢語和英語)。 結合一個检索系统以能力解決语言障隘是富挑戰性任務。
在我們的研究的每個科學文件被劃分成4個領域：標題、主題詞、摘要和被援引的參考。要計算每個領域相似度我們使用一個不同的演算法。我們的方法學的結果表示，我們的方法學能準確地檢索雙語文件。

Electronic documents have grown tremendously in quantity nowadays, the internet technology enable users to share information and knowledge independently. The language which is used to write the documents might also variant. This phenomenon has leads us to develop a methodology which can retrieved documents precisely and with the ability to solve language barrier.
In this research we develop a similarity-based methodology to retrieve bilingual scientific documents from Theses and Dissertation System. We compute the similarity of bilingual documents (Chinese and English). Integrated a retrieval system with the ability to solve language barrier is a challenging tasks.
Every scientific document in our research is divided into 4 fields which are: Title, Keyword, Abstract, and Cited Reference. To compute a similarity of every field we used a different technique. The result of our methodology shows that our methodology is able to retrieve bilingual documents accurately.

References
[1] Amer-Yahia, S., Botev, C. and Shanmugasundaram, J., 2004. TeXQuery: A Full-Text Search Extension to XQuery. In Proceedings International WWW Conference, New York, USA.
[2] Utsuro Takehito., Ikeda Illiroshi., Yamane Masaya., 2003. Bilingual Text, Matching using Bilingual Dictionary and Statistics.
[3] Baeza-Yates, R. and Ribeiro-Neto, B., 1999. Modern Information Retrieval. New York: The ACM Press.
[4] Buckley, C., SMART, Version 7.
[5] Callan, J.P., Croft, W.B. and Harding, S.M., 1995. The INQUERY Retrieval System. In DEXA 3. International Conferrence on Database and Expert Systems Applications, pp. 83-97, Berlin: Springer Verlag.
[6] Cohen, W., June 1998. Integration of Heterogeneous databases Without Common Domains Using Queries Based on Textual Similarity. In Proceeding ACM SIGMOD, 27(2): pp. 201-212, Seattle, WA.
[7] CORDIS: Community Research & Development Information Service, http://www.cordis.lu/en/home.html.
[8] Cutting, D. and Pedersen, J., 1990. Optimizations for Dynamic Inverted Index Maintenance. The 13th International Conference on Research and Development in Information Retrieval, pp. 405-411.
[9] Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K. and Harshman, R., 1990. Indexing by Latent Semantic analysis. Journal of the American Society for Information Sciences, 41, 6, pp. 391-407.
[10] Dickson, G.W., Senn, J.A. and Chervany, N.L., May 1977. Research in Management Information Systems: The Minnesota Experiments. Management Science, vol. 23, no. 9, pp. 913-923.
[11] Doszkocs, T.E., 1983. From Research to Application: The CITE Natural Language Information Retrieval System. In Research and Development in Information Retrieval, Salton, G. and Schneider, H.J., eds. (Lecture Notes in Computer Science Series, 146) Berlin: Springer-Verlag, pp. 251-262.
[12] Dumais, S.T., 1991. Improving the retrieval of information from external sources. Behavior Research Methods, Instruments & Computers, vol. 23, no. 2, pp. 229-236.
[13] Ellman, J., 2000. Using Roget''s Thesaurus to Determine the Similarity of Texts. Ph.D. Thesis, School of Computing, Engineering and Technology, University of Sunderland, England.
[14] Fagan, J.L., March 1989. The Effectiveness of a Nonsyntactic Approach to Automatic Phrase Indexing for Document Retrieval. Journal of the American Society for Information Science (ASIS), Vol. 40, Iss. 2, pp. 115-132.
[15] Fellbaum, C., 1998. WordNet: An Electronic Lexical Database. MIT Press, Cambridge, MA.
[16] Fontaine, A., May 1995. Sub-element indexing and probabilistic retrieval in the POSTGRES database system. Technical Report CSD-95-876, University of California at Berkeley. ftp://s2k-ftp.CS.Berkeley. EDU/pub/postgres/papers/.
[17] Fox, C., 1990. A stop list for general text. SIGIR Forum 20(12), pp. 19-35.
[18] Frakes, W.B. and Fox, C.J., 2003. Strength and similarity of affix removal stemming algorithms. SIGIR Forum 37(1): pp. 26-30.
[19] Geffet, M. and Feitelson, D.G., Jun 2001. Hierarchical indexing and document matching in BoW. In first ACM/IEEE Joint Conferrence Digital Libraries, pp. 259-267.
[20] George Allan Alderman III, M.A., 2000. Information Retrieval using an adaptive resonance theory (ART)-based Neural Net. Ph.D. dissertation, Georgetown University, UMI Number: 9978116.
[21] Grossman, D.A. and Frieder O., 1998. Information Retrieval: algorithms and heuristics. Boston: Kluwer.
[22] Hammouda, K. and Kamel, M., 2004. Document Similarity Using a Phrase Indexing Graph Model. Knowledge and Information Systems, vol. 6, no. 6, pp. 710-727.
[23] ISI Web of Knowledge, Version 3.0, http://isi01.isiknowledge.com/portal.cgi.
[24] Korfhage, R.R., 1997. Information Storage and Retrieval. N.Y.: John Wiley and Sons.
[25] Kowalski, G.J. and Maybury, M.T., 2000. Information Storage and Retrieval Systems: Theory and Implementation. Kluwer International Series on Information Retrieval, Inre 8. Kluwer Academic.
[26] Lee, K.H., Choy, Y.C. and Cho, S.B., 2004. An Efficient Algorithm to Compute Differences between Structured Documents. IEEE Transactions on Knowledge and Data Engineering, 16(8): pp. 965-979.
[27] Lin, D., 1997. Using Syntactic Dependency as Local Context to Resolve Word-Sense Ambiguity. In Proceedings of the Thirty-Fifth Annual Meeting of the Association for Computational Linguistics. Somerset, N.J.: Association for Computational Linguistics.
[28] Chen, Y.L., Wei, Jhong Jhih., Wu, Shin-Yi., Hu, Ya-Han., 2005. A Similarity-based method for retrieving documents from the SCI/SSCI database. Journal of Information Science.
[29] Meadow, C.T., Wang, J. and Stamboulie, M., 1993. An Analysis of Zipf-Mandelbrot Language Measures and Their Application to Artificial Languages. Journal of Information Science, 19(4): pp. 247-258.
[30] Meadow, C.T., Boyce, B.R., and Kraft, D.H., 2000. Text Information Retrieval Systems. 2nd edition. San Diego: Academic Press.
[31] Michaelj, A.B., 1997. Data Mining Techniques For Marketing, sales, and Customer Support. Wiley Computer Publishing.
[32] Miller, G., Beckwith, R., Fellbaum, C., Gross, D. and Miller, K., 1990. Introduction to WordNet: An on-line lexical database. J. Lexicography 3(4): pp. 235-244.
[33] Miller, G.A., 1995. WorldNet: a lexical database for English. Communications of the ACM, 38(11): pp. 39-41.
[34] Ng, H.T. and Zelle, J., 1997. Corpus based approaches to semantic interpretation in natural language processing. AI Magazine, 18(4): pp. 25-31.
[35] Palo Alto, C.A., 1987. Dialog Information Services. DIALOG System Seminar Manual, Problem Set 3.1.1, pp. 20.
[36] Gale, W.A. and Church, K. W. (1993). A program for aligning sentences in bilingual corpora, Computation Linguisties 19(1): 75 102.
[37] Gale, W. and Church, K (1991). Identifying word correspondences in parallel texts, Proceeding of 4th DARPA speech and natural language Workshop, pp. 152-157.
[38] Littman, L. Michael., Dumais, Susan.T., Landaner, Thomas.K (1996). Automatic Cross-Language Information Retrieval using Latent Semantic Indexing.
[39] Gao, Jianfeng., Wu, Andi., Li, Mu., Huang, Chang-Ning (2006). Chinese Word Segmentation and Named Entity Recognition: A Pragmatic Approach. Association for Computational Linguistics
[40] Zanettin, Federico. 1998. Bilingual Comparable Corpora and the Training of Translators. Meta: Journal des traducteurs/Meta: Translators’ Journal, vol.43 n 4, 1998, p. 616-630.
[41] Navigli, Roberto. 2009. Word Sense Disambiguation: A survey. ACM Computing Surveys, Vol. 41, No. 2, Article 10.
[42] Lu, Xiaofei. 2007. Combining Machine Learning with Linguistic Heuristics for Chinese Word Segmentation. Departement of Linguistics and Applied Language Studies. Pennysylvania State University, USA.
[43] Bharati, Akshar., V, Sriram., A, Vamshi Krishna., Sangal, Rajeev., Bendre, Sushma. 2002. An algorithm for aligning Sentences in Bilingual Corpora Using Lexical Information.
[44] Zou, Feng., Wang, Fu Lee., Deng, Xiaotie., Han, Song. 2006. Automatic Identification of Chinese Stop Words. Computer Science Department, City University of Hong Kong Kowloon Tong, Hong Kong. Advances in Natural Language Processing Research in Computing Science 18, 2006, pp. 151 – 162.
[45] Brown, P.F., Cocke, J., Della Pietra, S.A., Della Pietra, V.J., Jelinek, F., Lafferty, J.D., Mercer, R.L., Roossin, P.S.: A statistical approach to machine translation. Computational Linguistics 16 (1990) 79-85
[46] Brown, P.F., Della Pietra, S.A., Della Pietra, V.J., Mercer, R.L.: The mathematics of statistical machine translation: Parameter estimation. Computational Linguistics 19 (1993) 263 - 311