References
- ANSI/NISO Z39.19-2005 (2010) Guidelines for the Construction, Format, and Management of Monolingual Controlled Vocabularies | NISO website. (n.d.). Retrieved from https://www.niso.org/publications/ansiniso-z3919-2005-r2010
- Antoniou, G., & van Harmelen, F. (2004). Web Ontology Language: OWL. In S. Staab & R. Studer (Eds.), Handbook on Ontologies (pp. 67–92). Springer. https://doi.org/10.1007/978-3-540-24750-0_4
- Chan, L.M., & Zeng, M.L. (2002). Ensuring interoperability among subject vocabularies and knowledge organization schemes: A methodological analysis. IFLA Journal, 28(5–6), 323–327. https://doi.org/10.1177/034003520202800519
- Doing-Harris, K.M., & Zeng-Treitler, Q. (2011). Computer-assisted update of a consumer health vocabulary through mining of social network data. Journal of Medical Internet Research, 13(2), e37. https://doi.org/10.2196/jmir.1636
- Eisner, R., Poulin, B., Szafron, D., Lu, P., & Greiner, R. (2005). Improving protein function prediction using the hierarchical structure of the gene ontology. 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 1–10. https://doi.org/10.1109/CIBCB.2005.1594940
- Francesconi, E., Faro, S., Marinai, E., & Peruginelli, G. (2008). A methodological framework for thesaurus semantic interoperability. In Proceeding of the Fifth European Semantic Web Conference, pp. 76–87. https://scholar.googleusercontent.com/scholar?q=cache:5lsA9SO1FxoJ:scholar.google.com/+Francesconi,+E.,+Faro,+S.,+Marinai,+E.,+%26+Perugi,+G.+(2008).+A+methodological+framework+for+thesaurus+semantic+interoperability.+In+Proceeding+of+the+Fifth+European+Semantic+Web+Conference+(pp.+76-87).&hl=en&as_sdt=0,39
- Greenberg, J., Losee, R., Agüera, J.R.P., Scherle, R., White, H., & Willis, C. (2011). HIVE: Helping interdisciplinary vocabulary engineering. Bulletin of the American Society for Information Science and Technology, 37(4), 23–26. https://doi.org/10.1002/bult.2011.1720370407
- He, Z., Chen, Z.W., Oh, S., Hou, J.H., & Bian, J. (2017). Enriching consumer health vocabulary through mining a social Q&A site: A similarity-based approach. Journal of Biomedical Informatics, 69, 75–85. https://doi.org/10.1016/j.jbi.2017.03.016
- Heath, T., & Bizer, C. (2011). Linked data: Evolving the web into a global data space. Synthesis Lectures on the Semantic Web: Theory and Technology, 1(1), 1–136. https://doi.org/10.2200/S00334ED1V01Y201102WBE001
- IOS Press Ebooks. (2001). MEDINFO 2001. In the Proceedings of the 10th World Congress on Medical Informatics. (n.d.). Retrieved from http://ebooks.iospress.nl/volume/medinfo-2001
- Isaac, A., Wang, S., Zinn, C., Matthezing, H., van der Meij, L., & Schlobach, S. (2009). Evaluating thesaurus alignments for semantic interoperability in the library domain. IEEE Intelligent Systems, 24(2), 76–86. https://doi.org/10.1109/MIS.2009.26
- Jiang, L., & Yang, C.C. (2015). Expanding consumer health vocabularies by learning consumer health expressions from online health social media. In N. Agarwal, K. Xu, & N. Osgood (Eds.), Social Computing, Behavioral-Cultural Modeling, and Prediction (pp. 314–320). Springer International Publishing. https://doi.org/10.1007/978-3-319-16268-3_36
- Kaisser, M., Hearst, M.A., & Lowe, J.B. (2008). Improving search results quality by customizing summary lengths. In Proceedings of ACL-08: HLT, 701–709. https://www.aclweb.org/anthology/P08-1080
- McCray, A.T., Aronson, A.R., Browne, A.C., Rindflesch, T.C., Razi, A., & Srinivasan, S. (1993). UMLS knowledge for biomedical language processing. Bulletin of the Medical Library Association, 81(2), 184–194.
- Miles, A., Matthews, B., Wilson, M., & Brickley, D. (2005). SKOS Core: Simple Knowledge Organisation for the Web. In Proceedings of the 2005 International Conference on Dublin Core and Metadata Applications: Vocabularies in Practice. pp. 3–10.
- Rubenstein, E. (2012). From social hygiene to consumer health: Libraries, health information, and the American public from the late nineteenth century to the 1980s. Library & Information History, 28(3), 202–219. https://doi.org/10.1179/1758348912Z.00000000016
- Salvadores, M., Alexander, P.R., Musen, M.A., & Noy, N.F. (2013). BioPortal as a dataset of linked biomedical ontologies and terminologies in RDF. Semantic Web, 4(3), 277–284.
- Shadbolt, N., Berners-Lee, T., & Hall, W. (2006). The semantic web revisited. IEEE Intelligent Systems, 21(3), 96–101. https://doi.org/10.1109/MIS.2006.62
- Singh, A., & Nakata, K. (2005). Hierarchical classification of web search results using personalized ontologies. In Proceedings of the 3rd International Conference On Universal Access in Human-Computer Interaction, 10.
- Slater, L.T., Gkoutos, G.V., & Hoehndorf, R. (2020). Towards semantic interoperability: Finding and repairing hidden contradictions in biomedical ontologies. bioRxiv 2020.05.16.099309. https://doi.org/10.1101/2020.05.16.099309
- Smith, C.A., & Wicks, P.J. (2008). PatientsLikeMe: Consumer health vocabulary as a folksonomy. AMIA Annual Symposium Proceedings, 2008, 682–686.
- Turney, P.D. (2001). Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL. In L. De Raedt & P. Flach (Eds.), Machine Learning: ECML 2001 (Vol. 2167, pp. 491–502). Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-44795-4_42
- Zeng, M.L. (2019). Interoperability. Knowledge Organization, 46(2), 122–146. https://doi.org/10.5771/0943-7444-2019-2-122
- Zeng, Q., Tse, T., Divita, G., Keselman, A., Crowell, J., Browne, A., Goryachev, S., & Ngo, L. (2007). Term identification methods for consumer health vocabulary development. Journal of Medical Internet Research, 9(1), e4. https://doi.org/10.2196/jmir.9.1.e4