Abstract
Knowledge retrieval in the collaborative design of modern products has become a major factor in improving the efficiency of collaborative design. In this chapter, three different levels of knowledge retrieval approaches are introduced. In the first level, the keyword-based retrieval method for the textual information is described with theories and methods from the IR (Information Retrieval) domain. In the second level, the retrieval of structured design knowledge is presented to improve the retrieval performance, which includes generating summaries for knowledge nodes and filtering retrieval results based on type and status information, finding groups of nodes to achieve better match, and using complex queries to enable users better express knowledge needs. In the third level, the semantic retrieval of design knowledge is illustrated, which aims to enable the system to understand the meanings and contexts of knowledge nodes, the intents behind a user’s queries, and the context in which a request for information is being made. As demonstrated in the evaluations of the prototype system, the retrieval methods developed are effective and achieve good performance in addition to the intelligent assistance offered by the Design Rationale editor tool.
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References
Manning, C., Raghavan, P., & Schütze, H. (2010). Introduction to information retrieval. Natural Language Engineering, 16(1), 100–103.
Church, K. W. (2017). Word2Vec. Natural Language Engineering, 23(1), 155–162.
Peters, M. E., Neumann, M., Iyyer, M., Gardner, M., Clark, C., & Lee, K. (2018). Deep contextualized word representations. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) (pp. 2227–2237).
Kenton, J. D. M. W. C., & Toutanova, L. K. (2019, May). Bert: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) (pp. 4171–4186).
Bracewell, R., Wallace, K., Moss, M., & Knott, D. (2009). Capturing design rationale. Computer-Aided Design, 41(3), 173–186.
Bracewell, R. H., Ahmed, S., & Wallace, K. M. (2004, January). DRed and design folders: A way of capturing, storing and passing on knowledge generated during design projects. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (Vol. 46946, pp. 235–246).
Peng, G., Wang, H., Zhang, H., Zhao, Y., & Johnson, A. L. (2017). A collaborative system for capturing and reusing in-context design knowledge with an integrated representation model. Advanced Engineering Informatics, 33, 314–329.
Kim, S., Bracewell, R. H., & Wallace, K. M. (2005). A framework for design rationale retrieval. In DS 35: Proceedings ICED 05, the 15th International Conference on Engineering Design, Melbourne, Australia, August 15–18, 2005 (pp. 252–253).
Pantel, P., & Lin, D. (2002, July). Discovering word senses from text. In Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 613–619).
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Wang, H., Peng, G. (2023). Collaborative Design Knowledge Retrieval. In: Collaborative Knowledge Management Through Product Lifecycle. Springer, Singapore. https://doi.org/10.1007/978-981-19-9626-9_4
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DOI: https://doi.org/10.1007/978-981-19-9626-9_4
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