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New Technology of Library and Information Service  2015, Vol. 31 Issue (5): 1-7    DOI: 10.11925/infotech.1003-3513.2015.05.01
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Review on Semantic Retrieval System for Scientific Literature
Wang Ying, Wu Zhenxin, Xie Jing
National Science Library, Chinese Academy of Sciences, Beijing 100190, China
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Abstract  

[Objective] To investigate and summarize the typical semantic retrieval system for scientific literature. [Coverage] Use literatures related to semantic search retrieved by Web of Knowledge or Google Scholar, references and research reports of semantic retrieval systems. [Methods] This paper classifies current systems into four categories according to the degree of semantic processing, semantic query expansion retrieval system, concepts or entities centered retrieval system, relation-centered retrieval system, and retrieval system for knowledge discovery. [Results] The authors propose a basic framework of semantic retrieval systems for scientific literature, and summarize the features of semantic retrieval systems for scientific literature. [Limitations] Lack of performance evaluation of semantic retrieval system. [Conclusions] It provides a good guide for developing a semantic retrieval system for the scientific literature.

Key wordsSemantic search      Scientific literature      Text mining     
Received: 29 January 2015      Published: 11 June 2015
:  G250.76  

Cite this article:

Wang Ying, Wu Zhenxin, Xie Jing. Review on Semantic Retrieval System for Scientific Literature. New Technology of Library and Information Service, 2015, 31(5): 1-7.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2015.05.01     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2015/V31/I5/1

[1] Lu Z, Kim W, Wilbur W J. Evaluation of Query Expansion Using MeSH in PubMed [J]. Information Retrival, 2009, 12(1): 69-80.
[2] Griffon N, Chebil W, Rollin L, et al. Performance Evaluation of Unified Medical Language System®'s Synonyms Expansion to Query PubMed [J]. BMC Medical Informatics and Decision Making, 2012(12). doi: 10.1186/1472-6947-12-12.
[3] Matos S, Arrais J P, Maia-Rodrigues J, et al. Concept-based Query Expansion for Retrieving Gene Related Publications from MEDLINE [J]. BMC Bioinformatics, 2010(11). doi: 10. 1186/1471-2105-11-212.
[4] Bettembourg C, Diot C, Burgun A, et al. GO2PUB: Querying PubMed with Semantic Expansion of Gene Ontology Terms [J]. Journal of Biomedical Semantics, 2012, 3(1). doi: 10. 1186/2041-1480-3-7.
[5] Doms A, Schroeder M. GoPubMed: Exploring PubMed with the Gene Ontology [J]. Nucleic Acids Research, 2005 (33, Web Sever Issue): W783-W786.
[6] Kupershmidt I, Su Q J, Grewal A, et al. Ontology-based Meta-analysis of Global Collections of High-throughput Public Data [J]. PLoS One, 2010, 5(9). DOI: 10.1371/journal. pone.0013066.
[7] Nobata C, Sasaki Y, Okazaki N, et al. Semantic Search on Digital Document Repositories Based on Text Mining Results [C]. In: Proceedings of International Conferences on Digital Libraries and the Semantic Web 2009 (ICSD2009). 2009: 34-48.
[8] Coppernoll-Blach P. Quertle: The Conceptual Relationships Alternative Search Engine for PubMed [J]. Journal of Medical Library Association, 2011, 99(2): 176-177.
[9] Frijters R, Heupers B, van Beek P, et al. A Literature-based Keyword Enrichment Tool for Microarray Data Analysis [J]. Nucleic Acids Research, 2008 (36, Web Server Issue): W406-W410.
[10] Cheng D, Knox C, Young N, et al. PolySearch: A Web-based Text Mining System for Extracting Relationships Between Human Diseases, Genes, Mutations, Drugs and Metabolites [J]. Nucleic Acids Research, 2008 (36,Web Server Issue): W399-W405.
[11] Fleuren W W, Verhoeven S, Frijters R, et al. CoPub Update: CoPub 5.0 a Text Mining System to Answer Biological Questions [J]. Nucleic Acids Research, 2011 (39, Web Server Issue): W450-W454.
[12] Tsuruoka Y, Miwa M, Hamamoto K, et al. Discovering and Visualizing Indirect Associations Between Biomedical Concepts [J]. Bioinformatics, 2011, 27 (13): i111-i119.
[13] Ananiadou S. Advances of Biomedical Text Mining for Semantic Search [C]. In: Proceedings of the 2nd International Workshop on Web Science and Information Exchange in the Medical Web (MedEx'2011), Glasgow, UK. 2011.
[14] Wiley Online Library. The Smart Article: Introducing New and Enhanced Article Tools for Chemistry Content [EB/OL]. [2014-10-13]. http://onlinelibrary.wiley.com/subject/code/000128/ homepage/new.htm.
[15] Lu Z. PubMed and Beyond: A Survey of Web Tools for Searching Biomedical Literature [J]. Database: The Journal of Biological Databases and Curation, 2011. doi: 10.1093/ database/baq036.
[16] Rebholz-Schuhmann D, Kirsch H, Arregui M, et al. EBIMed-text Crunching to Gather Facts for Proteins from Medline [J]. Bioinformatics, 2007, 23(2): e237-e244.
[17] Wei C H, Kao H Y, Lu Z. PubTator: A Web-based Text Mining Tool for Assisting Biocuration [J]. Nucleic Acids Research, 2013(41,Web Server Issue): W518-W522.
[18] Bizer C, Heath T, Berners-Lee T. Linked Data-The Story So Far [J]. International Journal on Semantic Web and Information Systems, 2009, 5(3): 1-22.
[19] Fogarolli A, Keizer J, Anibaldi S, et al. AGRIS-From a Bibliographic Database to a Semantic Data Service on Agricultural Research Information [J]. Agricultural Information Worldwide, 2010, 3(1): 26-30.
[20] Yagoda A. Elsevier Health Sciences: Smart Content Drives Smart Applications Using Knowledge in Healthcare [EB/OL]. [2014-11-19]. http://www.w3.org/wiki/images/9/96/HCLSIG %24%24Meetings%24%242012-05-08_AlanYagoda.pdf.
[21] Doszkocs T. Semantic Search and Discovery [EB/OL]. [2014-10-13]. http://cendi.dtic.mil/presentations/01_12_2012_Doszkocs. pdf.
[22] Schneider A, Landefeld R, Wermter J, et al. Do Users Appreciate Novel Interface Features for Literature Search? [C]. In: Proceedings of the 2009 IEEE International Conference on Systems, Man and Cybernetics. 2009: 2062-2067.
[23] Wang J, Cetindil I, Ji S, et al. Interactive and Fuzzy Search: A Dynamic Way to Explore MEDLINE [J]. Bioinformatics, 2010, 26(18): 2321-2327.

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