This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
Belohlavek, R., & Vychodil, V. (2009). Formal concept analysis with background knowledge: Attribute priorities. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 39(4), 399–409.BelohlavekR.VychodilV.2009Formal concept analysis with background knowledge: Attribute priorities39439940910.1109/TSMCC.2008.2012168Search in Google Scholar
Carpineto, C., & Romano, G. (2004). Concept data analysis: Theory and applications. John Wiley & Sons.CarpinetoC.RomanoG.2004John Wiley & Sons10.1002/0470011297Search in Google Scholar
Chang, Y.W., & Huang, M.H. (2012). A study of the evolution of interdisciplinarity in library and information science: Using three bibliometric methods. Journal of the American Society for Information Science and Technology, 63(1), 22–33.ChangY.W.HuangM.H.2012A study of the evolution of interdisciplinarity in library and information science: Using three bibliometric methods631223310.1002/asi.21649Search in Google Scholar
Cimiano, P., Hotho, A., & Staab, S. (2005). Learning concept hierarchies from text corpora using formal concept analysis. Journal of Artificial Intelligence Research, 24, 305–339.CimianoP.HothoA.StaabS.2005Learning concept hierarchies from text corpora using formal concept analysis2430533910.1613/jair.1648Search in Google Scholar
Dong, K., Xu, H., Luo, R., Wei, L., & Fang, S. (2018). An integrated method for interdisciplinary topic identification and prediction: A case study on information science and library science. Scientometrics, 115(2), 849–868.DongK.XuH.LuoR.WeiL.FangS.2018An integrated method for interdisciplinary topic identification and prediction: A case study on information science and library science115284986810.1007/s11192-018-2694-xSearch in Google Scholar
Ganter, B., & Wille, R. (2012). Formal concept analysis: Mathematical foundations. Springer Science & Business Media.GanterB.WilleR.2012Springer Science & Business MediaSearch in Google Scholar
Ganter, B., & Wille, R. (1997). Applied lattice theory: Formal concept analysis. In General Lattice Theory, G. Grätzer editor, Birkhäuser.GanterB.WilleR.1997Applied lattice theory: Formal concept analysisBirkhäuser10.1007/978-3-0348-9326-8Search in Google Scholar
Gao, J.F. (2015). Coupling network literature knowledge discovery based on concept lattice. Library science research, 56(17), 122–125.GaoJ.F.2015Coupling network literature knowledge discovery based on concept lattice5617122125Search in Google Scholar
Hammarfelt, B. (2011). Interdisciplinarity and the intellectual base of literature studies: Citation analysis of highly cited monographs. Scientometrics, 86(3), 705–725.HammarfeltB.2011Interdisciplinarity and the intellectual base of literature studies: Citation analysis of highly cited monographs86370572510.1007/s11192-010-0314-5Search in Google Scholar
Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for information Science, 24(4), 265–269.SmallH.1973Co-citation in the scientific literature: A new measure of the relationship between two documents24426526910.1002/asi.4630240406Search in Google Scholar
Jia, C.Y., & Ni, X.J. (2003). Association rule mining: A survey. Computer Science, 30(4), 145–148.JiaC.Y.NiX.J.2003Association rule mining: A survey304145148Search in Google Scholar
Klein, J.T. (2000). A conceptual vocabulary of interdisciplinary science. Practising interdisciplinarity, 3–24.KleinJ.T.2000A conceptual vocabulary of interdisciplinary science3–2410.3138/9781442678729-003Search in Google Scholar
Kumar, C. (2011). Knowledge discovery in data using formal concept analysis and random projections. International Journal of Applied Mathematics and Computer Science, 21(4), 745–756.KumarC.2011Knowledge discovery in data using formal concept analysis and random projections21474575610.2478/v10006-011-0059-1Search in Google Scholar
Lahcen, B., & Kwuida, L. (2010). Lattice miner: A tool for concept lattice construction and exploration. Suplementary Proceeding of International Conference on Formal concept analysis (ICFCA’10).LahcenB.KwuidaL.2010Lattice miner: A tool for concept lattice construction and exploration10.1007/978-3-642-11928-6Search in Google Scholar
Leydesdorff, L., & Rafols, I. (2011). Indicators of the interdisciplinarity of journals: Diversity, centrality, and citations. Journal of Informetrics, 5(1), 87–100.LeydesdorffL.RafolsI.2011Indicators of the interdisciplinarity of journals: Diversity, centrality, and citations518710010.1016/j.joi.2010.09.002Search in Google Scholar
Leydesdorff, L., Rafols, I., & Chen, C. (2013). Interactive overlays of journals and the measurement of interdisciplinarity on the basis of aggregated journal–journal citations. Journal of the American Society for Information Science and Technology, 64(12), 2573–2586.LeydesdorffL.RafolsI.ChenC.2013Interactive overlays of journals and the measurement of interdisciplinarity on the basis of aggregated journal–journal citations64122573258610.1002/asi.22946Search in Google Scholar
Li, C.L., Liu, F.F., & Guo, F.J. (2013). Analysis on interdisciplinary research topics with cfinder of overlapping communities visualization software—taking the information science and computer science for example. Library and Information Service, 57(7), 75–80.LiC.L.LiuF.F.GuoF.J.2013Analysis on interdisciplinary research topics with cfinder of overlapping communities visualization software—taking the information science and computer science for example5777580Search in Google Scholar
Liu, P., & Wang, Z. (2012). A new method for detecting or ganizational knowledge structure: Author keyword coupling analysis based on FCA. Library and Information Service, 56(22), 121–128.LiuP.WangZ.2012A new method for detecting or ganizational knowledge structure: Author keyword coupling analysis based on FCA5622121128Search in Google Scholar
Liu, P., & Wu, Q. (2014). Detecting disciplinary knowledge structure based on formal concept analysis: An empirical investigation on library and information science, 58(18), 50–65.LiuP.WuQ.201458185065Search in Google Scholar
Min, C., & Sun, J.J. (2014). Clustering analysis on discipline-crossing research hotspots: An example of library and information science and journalism and communication studies. Library and Information Service, 58(1), 109–116.MinC.SunJ.J.2014Clustering analysis on discipline-crossing research hotspots: An example of library and information science and journalism and communication studies581109116Search in Google Scholar
Porter, A.L., Roessner, J.D., & Heberger, A.E. (2008). How interdisciplinary is a given body of research. Research Evaluation, 17(4), 273–282.PorterA.L.RoessnerJ.D.HebergerA.E.2008How interdisciplinary is a given body of research17427328210.3152/095820208X364553Search in Google Scholar
Porter A, Zhang Y. Text clumping for technical intelligence. Theory & Applications for Advanced Text Mining, 2012.PorterAZhangYText clumping for technical intelligence201210.5772/50973Search in Google Scholar
Reuters, T. (2016). Science citation index expanded. http://ip-science.thomsonreuters.com/mjl/scope/scope_scie/ReutersT.2016http://ip-science.thomsonreuters.com/mjl/scope/scope_scie/Search in Google Scholar
Schummer, J. (2004). Multidisciplinarity, interdisciplinarity and patterns of research collaboration in nanoscience and nanotechnology. Scientometrics, 59(3), 425–465.SchummerJ.2004Multidisciplinarity, interdisciplinarity and patterns of research collaboration in nanoscience and nanotechnology59342546510.1023/B:SCIE.0000018542.71314.38Search in Google Scholar
Shao, Z.Y., & Li, X.X. (2015). Detecting interdisciplinary knowledge structure based on concept lattice and bibliographic coupling. Library and Information Service, 59(8), 78–86.ShaoZ.Y.LiX.X.2015Detecting interdisciplinary knowledge structure based on concept lattice and bibliographic coupling5987886Search in Google Scholar
Stumme, G. (2009). Formal concept analysis. In: Staab S., Studer R. (eds) Handbook on Ontologies. Springer Berlin Heidelberg, 177–199.StummeG.2009StaabS.StuderR.Springer Berlin Heidelberg177–19910.1007/978-3-540-92673-3_8Search in Google Scholar
Teng, G.Q. (2012). Research on knowledge organization based on concept lattice of digital library. Changchun: Jilin University.TengG.Q.2012ChangchunJilin UniversitySearch in Google Scholar
Teng, G.Q., & Bi, Q. (2010). Comparative study on ConExp and lattice miner. New Technology of Library and Information Service, 26(10), 17–22.TengG.Q.BiQ.2010Comparative study on ConExp and lattice miner26101722Search in Google Scholar
Teng, G.Q, Bi, Q., & Bao, Y.L. (2011). An analysis on keywords of literature based on granularity concept analysis—A case study of ontology. New Technology of Library and Information Service. 27(9), 1–6.TengG.QBiQ.BaoY.L.2011An analysis on keywords of literature based on granularity concept analysis—A case study of ontology27916Search in Google Scholar
Derwent Data Analyzer. (2018). Retrieved from https://www.thevantagepoint.com/tda-home.html2018Retrieved fromhttps://www.thevantagepoint.com/tda-home.htmlSearch in Google Scholar
Venter, F.J., Oosthuizen, G.D., & Roos, J.D. (1997). Knowledge discovery in databases using lattices. Expert Systems With Applications, 13(4), 259–264.VenterF.J.OosthuizenG.D.RoosJ.D.1997Knowledge discovery in databases using lattices13425926410.1016/S0957-4174(97)00047-XSearch in Google Scholar
Wille, R. (2002). Why can concept lattices support knowledge discovery in databases? Journal of Experimental & Theoretical Artificial Intelligence, 14(2–3), 81–92.WilleR.2002Why can concept lattices support knowledge discovery in databases?142–3819210.1080/09528130210164161Search in Google Scholar
Wille, R. (2009). Restructuring lattice theory: An approach based on hierarchies of concepts. Formal Concept Analysis. Springer Berlin Heidelberg.WilleR.2009Springer Berlin Heidelberg10.1007/978-3-642-01815-2_23Search in Google Scholar
Xu, H.Y., Guo, T., Yue, Z.H., Ru, L.J., & Fang, S. (2016). Interdisciplinary topics of information science: A study based on the terms interdisciplinarity index series. Scientometrics, 106(2), 583–601.XuH.Y.GuoT.YueZ.H.RuL.J.FangS.2016Interdisciplinary topics of information science: A study based on the terms interdisciplinarity index series106258360110.1007/s11192-015-1792-2Search in Google Scholar
Xu, H.Y., Liu, C.J., Lei, B.X., Li, H.L., & Fang, S. (2014). Measurement visualization and application of interdisciplinary research. Library and Information Service, 58(12), 95–101.XuH.Y.LiuC.J.LeiB.X.LiH.L.FangS.2014Measurement visualization and application of interdisciplinary research581295101Search in Google Scholar
Xu, H.Y., Yin, C.X., Guo, T., Tan, X., & Fang, S. (2015). Interdisciplinary research review. Library and Information Service, 59(5), 119–127.XuH.Y.YinC.X.GuoT.TanX.FangS.2015Interdisciplinary research review595119127Search in Google Scholar
Serhiy, A. Yevtushenko (2000). System of data analysis “Concept Explorer”. Proceedings of the 7th national conference on Artificial Intelligence KII-2000, p. 127–134.SerhiyA. Yevtushenko2000System of data analysis “Concept Explorer”127–134Search in Google Scholar
Zhang, H.L., Wei, J.X., Du, Z.D., Liu, X., YAN, S., Feng, Z., Li, X.D., & Feng, X.F. (2011). Interdisciplinary research based on social complex network. Journal of Intelligence, 30(10), 25–29.ZhangH.L.WeiJ.X.DuZ.D.LiuX.YANS.FengZ.LiX.D.FengX.F.2011Interdisciplinary research based on social complex network30102529Search in Google Scholar
Zhang, Z.Q., & Fan, S.P. (2015). On the emergence and development of subject informatics. Journal of The China Society for Scientific and Technical Information, 34(10), 1011–1023.ZhangZ.Q.FanS.P.2015On the emergence and development of subject informatics341010111023Search in Google Scholar