Abstract
This paper aims to explain the construction strategy of interdisciplinary knowledge centers from the perspective of expert systems, knowledge management and educational information technology. The method is: Firstly, it explores how to construct the strategy of interdisciplinary knowledge centers sharing, and then makes necessary explorations from computer assisted knowledge management, expert knowledge acquisition and educational autonomous learning. Finally, establish the foundation of natural language understanding in the domain knowledge base which is the basis of the interdisciplinary knowledge center. It is characterized by the application of the wisdom system studied strategy, with machine translation, machine learning and human-computer interaction, starting from the excellent courses in research universities, with the combination of intelligent text analysis and knowledge module finishing, and with the application of “seven-stapes pass” and “eight-persons group” as the education management innovation paradigm. The result is the new paradigm with both standardization and individuality, namely the construction of an interdisciplinary knowledge center that combines large production with small production. The significance lies in the combination of “language, knowledge, software, hardware formal system engineering” and “education, management, learning, application social system engineering”, that help to promote the interdisciplinary knowledge center and its systems engineering talents training. It is more efficient to build the smart systems studied for serving the society.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Aztiria, A., et al.: Learning patterns in ambient intelligence environments: a survey. Artif. Intell. Rev. 34(1), 35–51 (2010)
Madden, M.G., et al.: Transfer of experience between reinforcement learning environments with progressive difficulty. Artif. Intell. Rev. 21(3–4), 375–398 (2004)
Snow, C., et al.: Network EducationWare: an open-source web-based system for synchronous distance education. IEEE Trans. Educ. 48(4), 705–712 (2005)
Graetz, C., et al.: Toothbrushing education via a smart software visualization system. J. Periodontol. 84(2), 186–195 (2013)
Fox, B.I., et al.: Knowledge, skills, and resources for pharmacy informatics education. Am. J. Pharm. Educ. 75(5), 93 (2011)
Tofade, T., et al.: Use of SMART learning objectives to introduce continuing professional development into the pharmacy curriculum. Am. J. Pharm. Educ. 76(4), 68 (2012)
Wen, C., et al.: Design of a microlecture mobile learning system based on smartphone and web platforms. IEEE Trans. Educ. 58(3), 203–207 (2015)
Hu, Q., et al.: A smart home test bed for undergraduate education to bridge the curriculum gap from traditional power systems to modernized smart grids. IEEE Trans. Educ. 58(1), 32–38 (2015)
Fjortoft, N., et al.: Smartphones, memory, and pharmacy education. American Journal of Pharmaceutical Education, 2018:ajpe7054
Lehto, M.R., et al.: Scientific knowledge acquisition during the extension of GSA: an expert system for generic safety analysis. Int. J. Ind. Ergon. 2(1), 61–75 (1987)
Marcus, S.: SALT: a knowledge-acquisition tool for propose-and-revise systems. Artif. Intell. 39(1), 1–37 (1988)
Compton, P., et al.: Ripple down rules: turning knowledge acquisition into knowledge maintenance. Artif. Intell. Med. 4(6), 463–475 (1992)
Birmingham, W., et al.: Knowledge-acquisition tools with explicit problem-solving models. Knowl. Eng. Rev. 8(1), 5–25 (1993)
Wagner, W.P., et al.: Knowledge acquisition for expert systems in accounting and financial problem domains. Knowl.-Based Syst. 15(8), 439–447 (2002)
Kasabov, N.K., et al.: Fu N N/2—a fuzzy neural network architecture for adaptive learning and knowledge acquisition. Inf. Sci. 101(3), 155–175 (2012)
Prado, R.P., et al.: On providing quality of service in grid computing through multi-objective swarm-based knowledge acquisition in fuzzy schedulers. Int. J. Approx. Reason. 53(2), 228–247 (2012)
Leu, G., et al.: A multi-disciplinary review of knowledge acquisition methods: from human to autonomous eliciting agents. Knowl.-Based Syst. 105(9), 1–22 (2016)
Shult, D.: Augmenting course quality through the use of videotapes. Am. J. Phys. 49(4), 344 (1981)
Poirier, T.I., et al.: Use of web technology and active learning strategies in a quality assessment methods course. Am. J. Pharm. Educ. 64(3), 289–294 (2000)
Stevenson, T.L., et al.: A quality improvement course review of advanced pharmacy practice experiences. Am. J. Pharm. Educ. 75(6), 116 (2011)
Kesari, K., et al.: Integrating residents with institutional quality improvement teams. Med. Educ. 51, 1173 (2017)
Porter, A.L., et al.: Development of a holistic assessment plan to evaluate a four-semester laboratory course series. Am. J. Pharm. Educ. 81(2), 33 (2017)
Bonnes, S.L., et al.: Flipping the quality improvement classroom in residency education. Acad. Med. 92(1), 101 (2017)
Hessler, M., et al.: Availability of cookies during an academic course session affects evaluation of teaching. Med. Educ. 52(6), 1064–1072 (2018)
Bastian, K.C., et al.: Does quantity affect quality? teachers’ course preparations and effectiveness. J. Res. Educ. Eff. 1–45 (2018)
Zou, S., Zou, X.: On the forward-looking nature of contemporary science general education in the perspective of fairness - the enlightenment from “Science for All Americans”. In: The 2nd Capital University Higher Education Graduate Academic Forum Proceedings 2011 (2011)
Zou, X., et al.: The new mission of contemporary chinese universities: cultural heritage and innovation based on chinese thinking and bilingual processing. v 25(5), 106–113 (2012)
Xiaohui, Z., Shunpeng, Z.: Two major categories of formal strategy. Comput. Appl. Softw. 24(16), 3086–3114 (2013)
Zou, S., et al.: Understanding: how to resolve ambiguity. In: Shi, Z. (eds.) Intelligence Science I. ICIS 2017, vol. 510. Springer, Cham (2017)
Zou, S., et al.: How to do knowledge module finishing. In: Shi, Z. (ed.), vol 539. Springer (2018)
Hua, W., et al.: Using two formal strategies to eliminate ambiguity in poetry text, vol 539. Springer (2018)
Xu, W., et al.: The cognitive features of programming language and natural language, vol 539. Springer (2018)
Luo X., et al.: The cognitive features of interface language and user language, vol 539. Springer (2018)
Maimaiti, M., et al.: Discussion on bilingual cognition in international exchange activities, vol 539. Springer (2018)
Wang, G., et al.: Language understanding of the three groups of connections, vol 539. Springer (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Zou, X., Zou, S., Wang, X. (2020). The Strategy of Constructing an Interdisciplinary Knowledge Center. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_112
Download citation
DOI: https://doi.org/10.1007/978-3-030-32591-6_112
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-32590-9
Online ISBN: 978-3-030-32591-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)