A Method for Acquiring Experiential Engineering Knowledge from Online Engineering Forums

  • Zuhua JiangEmail author
  • Bo Song
  • Xiaoming Sun
  • Haili Wang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1084)


Question and answer (Q&A) is the most primitive and common way of knowledge exchange. There is a lot of empirical knowledge accumulated in the Q&A record of online engineering forums. In order to acquire experiential engineering knowledge from the Q&A record, first an ontology of experiential engineering knowledge is constructed by referring to authoritative and structured domain text, whereby a formal conceptualization of a specific engineering field is obtained. In view of the relatively lower quality of empirical Q&A compared with authoritative knowledge source, the quality of online Q&A in the field of computer-aided engineering is evaluated by referring to the relevant methods in the quality evaluation of community Q&A. Finally, by selecting high-quality Q&A and express it as ontology concepts and attributes, the acquisition of experiential engineering knowledge is achieved.


Knowledge acquisition Experiential engineering knowledge Online engineering forum Q&A 



This work was supported by National Natural Science Foundation of China (No. 71601113, 71671113).


  1. 1.
    Gavrilova, T., Andreeva, T.: Knowledge elicitation techniques in a knowledge management context. J. Knowl. Manage. 16(4), 523–537 (2012)CrossRefGoogle Scholar
  2. 2.
    Argote, L., Miron-Spektor, E.: Organizational learning: from experience to knowledge. Organ. Sci. 22(5), 1123–1137 (2011)CrossRefGoogle Scholar
  3. 3.
    Ruiz, P.P., Foguem, B.K., Grabot, B.: Generating knowledge in maintenance from Experience feedback. Knowl.-Based Syst. 68, 4–20 (2014)CrossRefGoogle Scholar
  4. 4.
    Chen, Y.J.: Development of a method for ontology-based empirical knowledge representation and reasoning. Decis. Support Syst. 50(1), 1–20 (2010)CrossRefGoogle Scholar
  5. 5.
    Liu, L., Jiang, Z., Song, B.: A novel two-stage method for acquiring engineering-oriented empirical tacit knowledge. Int. J. Prod. Res. 52(20), 5997–6018 (2014)CrossRefGoogle Scholar
  6. 6.
    Song, B., Jiang, Z., Liu, L.: Automated experiential engineering knowledge acquisition through Q&A contextualization and transformation. Adv. Eng. Inf. 30(3), 467–480 (2016)CrossRefGoogle Scholar
  7. 7.
    Blooma, M.J., Chua, A.Y.K., Goh, D.H.L.: A predictive framework for retrieving the best answer. In: Proceedings of the 2008 ACM Symposium on Applied Computing, pp. 1107–1111 (2008)Google Scholar
  8. 8.
    Shah, C., Pomerantz, J.: Evaluating and predicting answer quality in community QA. In: Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 411–418 (2010)Google Scholar
  9. 9.
    Nie, L., Wei, X., Zhang, D., et al.: Data-driven answer selection in community QA systems. IEEE Trans. Knowl. Data Eng. 29(6), 1186–1198 (2017)CrossRefGoogle Scholar
  10. 10.
    Gruber, T.R.: A translation approach to portable ontology specifications. Knowl. Acquis. 5(2), 199–220 (1993)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Zuhua Jiang
    • 1
    Email author
  • Bo Song
    • 2
  • Xiaoming Sun
    • 1
  • Haili Wang
    • 1
  1. 1.Department of Industrial Engineering and ManagementShanghai Jiao Tong UniversityShanghaiChina
  2. 2.China Institute of FTZ Supply ChainShanghai Maritime UniversityShanghaiChina

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