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Relevant bibliographies by topics / Full-Text Information Retrieval

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Academic literature on the topic 'Full-Text Information Retrieval'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Full-Text Information Retrieval"

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Sievert, MaryEllen C. "Full-text information retrieval: Introduction." Journal of the American Society for Information Science 47, no. 4 (1996): 261–62. http://dx.doi.org/10.1002/(sici)1097-4571(199604)47:4<261::aid-asi1>3.0.co;2-v.

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Kostoff, Ronald N. "Expanded information retrieval using full-text searching." Journal of Information Science 36, no. 1 (2009): 104–13. http://dx.doi.org/10.1177/0165551509353250.

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POSWICKosb, R. F. "Full-Text Retrieval on Microcomputers." Literary and Linguistic Computing 4, no. 2 (1989): 108–14. http://dx.doi.org/10.1093/llc/4.2.108.

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Blair, David C. "Full Text Retrieval: Evaluation and implications." KNOWLEDGE ORGANIZATION 13, no. 1 (1986): 18–23. http://dx.doi.org/10.5771/0943-7444-1986-1-18.

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Blair, David C., and M. E. Maron. "Full-text information retrieval: Further analysis and clarification." Information Processing & Management 26, no. 3 (1990): 437–47. http://dx.doi.org/10.1016/0306-4573(90)90102-8.

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Zillmann, Hartmut. "Information Retrieval and Search Engines in Full-text Databases." LIBER Quarterly 10, no. 3 (2000): 335. http://dx.doi.org/10.18352/lq.7605.

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Teufel, Bernd, and Stephanie Schmidt. "Full text retrieval based on syntactic similarities." Information Systems 13, no. 1 (1988): 65–70. http://dx.doi.org/10.1016/0306-4379(88)90027-0.

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Potthast, Martin, Benno Stein, and Matthias Hagen. "The information retrieval anthology 2021." ACM SIGIR Forum 55, no. 1 (2021): 1–18. http://dx.doi.org/10.1145/3476415.3476417.

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The Information Retrieval Anthology, IR Anthology for short, is an endeavor to create a comprehensive collection of metadata and full texts of IR-related publications. We report on its first release, the use cases it can serve, as well as the challenges lying ahead to develop it towards a resource that serves the IR community for years to come. The IR Anthology's metadata browser and full text search engine are available at IR.webis.de.

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Shi, Hui, and Jing Jing Cai. "The Design and Implementation of Database on the Full-Text Retrieval System of Multi Document." Applied Mechanics and Materials 556-562 (May 2014): 5964–67. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.5964.

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With the rapid development of information technology and people’s relying on information technology, a growth trend geometry has been showing by all kinds of electronic document format , a full-text retrieval system of multi document we was needed to be designed and implemented in order to retrieve the required information quickly and accurately among those vast amounts of information. During the design and implementation process in the system, it played a crucial role in the link to design and realize the database. The design and implementation of database development process part in the full-text retrieval system of multi document was mainly introduced in this paper.

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Tauchert, W., J. Hospodarsky, J. Krause, C. Schneider, and C. Womser‐Hacker. "Effects of linguistic functions on information retrieval in a German‐language full‐text database: comparison between retrieval in abstract and full text." Online Review 15, no. 2 (1991): 77–86. http://dx.doi.org/10.1108/eb024367.

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Dissertations / Theses on the topic "Full-Text Information Retrieval"

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Oyarce, Guillermo Alfredo. "A Study of Graphically Chosen Features for Representation of TREC Topic-Document Sets." Thesis, University of North Texas, 2000. https://digital.library.unt.edu/ark:/67531/metadc2456/.

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Document representation is important for computer-based text processing. Good document representations must include at least the most salient concepts of the document. Documents exist in a multidimensional space that difficult the identification of what concepts to include. A current problem is to measure the effectiveness of the different strategies that have been proposed to accomplish this task. As a contribution towards this goal, this dissertation studied the visual inter-document relationship in a dimensionally reduced space. The same treatment was done on full text and on three document representations. Two of the representations were based on the assumption that the salient features in a document set follow the chi-distribution in the whole document set. The third document representation identified features through a novel method. A Coefficient of Variability was calculated by normalizing the Cartesian distance of the discriminating value in the relevant and the non-relevant document subsets. Also, the local dictionary method was used. Cosine similarity values measured the inter-document distance in the information space and formed a matrix to serve as input to the Multi-Dimensional Scale (MDS) procedure. A Precision-Recall procedure was averaged across all treatments to statistically compare them. Treatments were not found to be statistically the same and the null hypotheses were rejected.

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Ďulík, Jan. "Vyhledávání informací pro vědecké portály." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-235546.

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This paper deals with the information retrieval in research portals with the intention of the retrieval in scientific publications. We define concepts related to the information retrieval, classification and knowledge representation. We also present existing search tools used as the initial inspiration for the design of the search intergace. Futhermore we describe the implementation as well as the process of collecting sample data. In the last chapter we discuss usability of the developed web application.

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Čeloud, David. "Vyhledávání informací TRECVid Search." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237260.

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The master's thesis deals with Information Retrieval. It summarizes the knowledge in the field of Information Retrieval theory. Furthermore, the work gives an overview of models used in Information Retrieval, the data and the actual issues and their possible solutions. The practical part of the master's thesis is focused on the implementation of methods of information retrieval in textual data. The last part is dedicated to experiments validating the implementation and its possible improvements.

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Brown, Eric William. "Execution performance issues in full-text information retrieval." 1996. https://scholarworks.umass.edu/dissertations/AAI9619375.

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The task of an information retrieval system is to identify documents that will satisfy a user's information need. Effective fulfillment of this task has long been an active area of research, leading to sophisticated retrieval models for representing information content in documents and queries and measuring similarity between the two. The maturity and proven effectiveness of these systems has resulted in demand for increased capacity, performance, scalability, and functionality, especially as information retrieval is integrated into more traditional database management environments. In this dissertation we explore a number of functionality and performance issues in information retrieval. First, we consider creation and modification of the document collection, concentrating on management of the inverted file index. An inverted file architecture based on a persistent object store is described and experimental results are presented for inverted file creation and modification. Our architecture provides performance that scales well with document collection size and the database features supported by the persistent object store provide many solutions to issues that arise during integration of information retrieval into more general database environments. We then turn to query evaluation speed and introduce a new optimization technique for statistical ranking retrieval systems that support structured queries. Experimental results from a variety of query sets show that execution time can be reduced by more than 50% with no noticeable impact on retrieval effectiveness, making these more complex retrieval models attractive alternatives for environments that demand high performance.

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Chang, Chan-Chia, and 張展嘉. "Using Free Syllable Decoding on Full-text Information Retrieval and Sentence Recognition." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/35207760927471776376.

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碩士<br>國立清華大學<br>資訊工程學系<br>90<br>In this thesis, we discuss the methods for constructing a Mandarin syllable-recognizer which can be used for diverse applications such as "full-text information retrieval" and "sentence recognition". The syllable-recognizer performs recognition tasks without using tone information and language models, leading to a low recognition rate at the syllable level. Hence we identify the associated problems and propose methods to deal these problems. The first problem is the low recognition rate at the syllable-level. The identified syllable might not be correct, but it bears similarity to the intended syllable. Therefore, we establish a "syllable-similarity table" to describe the similarity between any two syllables, and the similarity scores are used in ranking the possible output. The system''s performance becomes more robust after adding this enhancement. Another problem is the number of syllables this recognizer decoded may not be correct. The most common errors are "deletion error" and "insertion error". Different applications call for different strategies to deal with the problem. In sentence recognition, we apply the concept of "dynamic time warping" to make the string-matching process more flexible. In full-text information retrieval, we use the methods of "syllable intersection" and "syllable weights" to evaluate the score of each retrieved document.

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Tang, Xiaoya. "Extraction and use of structured information in full-text retrieval : a case study /." 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3301232.

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Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.<br>Source: Dissertation Abstracts International, Volume: 69-02, Section: A, page: 0417. Adviser: Linda C. Smith. Includes bibliographical references (leaves 210-217) Available on microfilm from Pro Quest Information and Learning.

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Chang, Yu-Jen, and 張佑任. "A Research of Performance Evaluation of Mandarin Chinese Full-Text Information Retrieval--Full-Text Scan Model vs. Cluster Indexing Model." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/31589747547714555995.

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碩士<br>南華大學<br>資訊管理學系碩士班<br>90<br>Full-Text Information Retrieval is becoming an interdisciplinary interest. Mandarin Chinese Full-Text Information Retrieval is facing more basic difficulties than English context because of research lag and language nature. Lack of an objective test collection and a standard effectiveness evaluation for information retrieval experiments is the fundamental issue for Mandarin Chinese Full-Text information retrieval. In this thesis, we will introduce two different systems, including the Chinese Text Processor (CTP) developed by Academia Sinica in 1996, and the Cluster Indexing Model (CIM) developed by Huang Yun-Long in 1997. Also we will use same corpus (documents set), to evaluate system performance. Concerning the research status in Chinese, this research will have three contributions. First, analysis the fitness method of Full-Text Information Retrieval in same corpus or documents set. Second, developing a mature Cluster Indexing Model as the fundamental of advance application researches. Finally, this project will construct test collections and a standard effectiveness evaluation for Full-Text Information Retrieval researches in Chinese. Involving with medicine of Children’s Daily News (502 documents) and 21 queries. Under a series of experiments, the following conclusions are discovered: 1.The average recall of CTP is 99.02%, and its average precision is 17.72%. 2.In automatic term segmentation methods, under index dimension 100 and similarity threshold 0.3： (1)The recall of CIM-IDF is 80.73%, and the precision is 45.09%. (2)The recall of CIM-TF is 65.97%, and the precision is 43.52%. 3.In manual term segmentation methods, under index dimension 100 and similarity threshold 0.3： (1)The recall of CIM-IDF is 82.81%, and the precision is 47.11%. (2)The recall of CIM—TF is 64.81%, and the precision is 42.72%. 4.According to the results of above experiments, the following conclusions are discovered: (1)The performance of CIM-IDF is better than CTP in automatic and manual term segmentation. (2)The performance of CIM-IDF is better than CIM—TF in automatic and manual term segmentation. (3)In CIM-IDF, when index dimension greater than 80, the results show that the performance of automatic and manual term segmentation are similar. It showed clearly that automatic term segmentation methods could substitute for manual. Many researchers have devoted to developing information retrieval systems for a long time. They are find new ways of doing things from different theories and improve system of performance, but not any one system can by satisfy. However, The IR system should support different retrieval models, and relevance feedback can use to differ model in the future. Besides, research has involved many topics for discussion in Mandarin Chinese Full-Text information retrieval. However, it was lack of effectiveness evaluation in diverse information retrieval. If research could construct a standard of evaluation environment (ex. large corpus, query, relevance judgment, and a standard of evaluation), it will improve system of performance to contributive.

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Gauch, Susan Evalyn. "An expert system for searching in full-text." 1990. http://books.google.com/books?id=aLPgAAAAMAAJ.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 1990.<br>eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 120-125).

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Books on the topic "Full-Text Information Retrieval"

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Tenopir, Carol. Retrieval performance in a full text journal article database. University Microfilms International, 1985.

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Xiao, Hemin. Using a thesaurus for query refinement in full-text retrieval. UW Centre for the New Oxford English Dicitionary [sic] and Text Research, 1994.

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Tenopir, Carol. Full text databases. Greenwood Press, 1990.

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Sabourin, Conrad. Computational linguistics in information science: Information retrieval (full-text or conceptual), automatic indexing, text abstraction, content analysis, information extraction, query languages : bibliography. Infolingua, 1994.

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Kristensen, Jaana. The effectiveness of a searching thesaurus in free-text searching of a full-text database. Tampereen yliopisto, Kirjastotieteen ja informatikan latios, 1990.

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Enhancing performance of full-text retrieval systems using relevance feedback. University Microfilms International, 1993.

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An evaluation of the applicability of ranking algorithms to improving the effectiveness of full text retrieval. University Microfilms International, 1986.

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Murray, Gerry. State of the full text retrieval market, 1996-2002 (AIIM international industry study). Aiim International, 1998.

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National Agricultural Library (U.S.). Evaluation of NAL full text databases: Final report. 1987.

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Kestenbaum, Ann. Case study of a small, specialized press agency: The storage, retrieval and enhancement of information download from full-text databases. 1989.

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Book chapters on the topic "Full-Text Information Retrieval"

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Zhang, Jinsong, Chun Guo, and Xiaozhong Liu. "Topic Based Author Ranking with Full-Text Citation Analysis." In Information Retrieval Technology. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35341-3_43.

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Belazzougui, Djamal, and Gonzalo Navarro. "Improved Compressed Indexes for Full-Text Document Retrieval." In String Processing and Information Retrieval. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24583-1_38.

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Ito, Masaru, Hiroshi Inoue, and Kenjiro Taura. "Fragmented BWT: An Extended BWT for Full-Text Indexing." In String Processing and Information Retrieval. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46049-9_10.

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Ohlebusch, Enno, Simon Gog, and Adrian Kügel. "Computing Matching Statistics and Maximal Exact Matches on Compressed Full-Text Indexes." In String Processing and Information Retrieval. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16321-0_36.

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Brown, Eric W., James P. Callan, W. Bruce Croft, and J. Eliot B. Moss. "Supporting full-text information retrieval with a persistent object store." In Advances in Database Technology — EDBT '94. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-57818-8_64.

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Boteva, Vera, Demian Gholipour, Artem Sokolov, and Stefan Riezler. "A Full-Text Learning to Rank Dataset for Medical Information Retrieval." In Lecture Notes in Computer Science. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30671-1_58.

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Jonassen, Simon, and Svein Erik Bratsberg. "A Combined Semi-pipelined Query Processing Architecture for Distributed Full-Text Retrieval." In Web Information Systems Engineering – WISE 2010. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17616-6_51.

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Anick, Peter G. "Adapting a Full-text Information Retrieval System to the Computer Troubleshooting Domain." In SIGIR ’94. Springer London, 1994. http://dx.doi.org/10.1007/978-1-4471-2099-5_36.

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Meng, Qingyuan, Min Chen, Jingsheng Li, Linzhi Zhang, and Shuming Dong. "Chinese Full-Text Retrieval Technology Applied in National Occupational Training and Testing Network in WWW Environment." In Information Systems in the WWW Environment. Springer US, 1998. http://dx.doi.org/10.1007/978-0-387-35347-0_12.

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"Retrieval from Full Text." In Human Information Retrieval. The MIT Press, 2009. http://dx.doi.org/10.7551/mitpress/8052.003.0006.

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Conference papers on the topic "Full-Text Information Retrieval"

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Anick, Peter G., and Rex A. Flynn. "Versioning a full-text information retrieval system." In the 15th annual international ACM SIGIR conference. ACM Press, 1992. http://dx.doi.org/10.1145/133160.133183.

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Wang, Song, and Yongping Xiong. "HECATE: A Full-Text Retrieval System for Short Text." In 2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016). Atlantis Press, 2016. http://dx.doi.org/10.2991/amitp-16.2016.75.

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Papapetrou, Odysseas. "Full-text indexing and information retrieval in P2P systems." In the 2008 EDBT Ph.D. workshop. ACM Press, 2008. http://dx.doi.org/10.1145/1387150.1387158.

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Salton, Gerard, J. Allan, and Chris Buckley. "Approaches to passage retrieval in full text information systems." In the 16th annual international ACM SIGIR conference. ACM Press, 1993. http://dx.doi.org/10.1145/160688.160693.

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Bast, Hannah, Florian Bäurle, Björn Buchhold, and Elmar Haußmann. "Semantic full-text search with broccoli." In SIGIR '14: The 37th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2014. http://dx.doi.org/10.1145/2600428.2611186.

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Lu, Xuebing, Yili Xu, Weiwei Deng, and Yingjie Yan. "Decryption of Full Text Retrieval Technology: Chinese Word Segmentation." In 2016 2nd International Conference on Materials Engineering and Information Technology Applications (MEITA 2016). Atlantis Press, 2017. http://dx.doi.org/10.2991/meita-16.2017.69.

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Li, Shengdong, Xueqiang Lv, Feng Ling, and Shuicai Shi. "Study on Efficiency of Full-Text Retrieval Based on Lucene." In 2009 International Conference on Information Engineering and Computer Science. IEEE, 2009. http://dx.doi.org/10.1109/iciecs.2009.5363389.

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Wang, Long, and Zhenkai Wan. "Secure P2P File Sharing System Based on Full-Text Retrieval." In 2009 First International Conference on Information Science and Engineering. IEEE, 2009. http://dx.doi.org/10.1109/icise.2009.1048.

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Chavez, Edgar, and Eric Tellez. "A Universal Full Text Index with Access Control and Annotation Driven Information Retrieval." In 2006 15th International Conference on Computing. IEEE, 2006. http://dx.doi.org/10.1109/cic.2006.17.

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Yeganova, Lana, Won Gyu Kim, Donald Comeau, W. John Wilbur, and Zhiyong Lu. "Measuring the relative importance of full text sections for information retrieval from scientific literature." In Proceedings of the 20th Workshop on Biomedical Language Processing. Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.bionlp-1.27.

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