Articles
Vol. 4, No. 2 (2026)
Sinatrio Bimo Wahyudi
,
Dana Indra Sensuse
,
Sofian Lusa
,
Muhammad Hafizh Qurani
,
Yordan Yasin
,
Icha Mailinda
,
Dana Indra Sensuse
,
Sofian Lusa
,
Muhammad Hafizh Qurani
,
Yordan Yasin
,
Icha Mailinda
10.58477/cj.v4i2.510
Published: 2026-08-30
Abstract
AI shopping assistants increasingly employ agent-based retrieval, combining lexical search, structured filtering, and LLM-mediated selection. However, effective retrieval often requires knowledge beyond textual matching. This exploratory single-case study of an Indonesian grocery e-commerce assistant triangulates 279 observations, 52 failure traces, 74 practitioner-reported defects, a schema audit, and four practitioner interviews. The analysis identifies six retrieval-critical knowledge dimensions and reveals that externalization fails at two distinct layers. At the product data-model layer, essential fields (allergens, dietary constraints, age suitability) were absent and persisted despite architectural changes. At the retrieval-schema layer, existing knowledge failed to reach candidates: structured filters appeared in only 29% of calls, and correctly invoked filters often returned empty sets from non-empty pools. Addressing these layer-specific failures, the study proposes a structured knowledge framework based on the knowledge management process cycle, positioning GraphRAG as a future direction.
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Vol. 4 No. 2 (2026)
How to Cite
How to Cite
Wahyudi, S. B., Sensuse, D. I., Lusa, S., Qurani, M. H., Yasin, Y., & Mailinda, I. (2026). Absent or Unretrievable: A Two-Layer Knowledge Management Framework for Retrieval-Critical Product Knowledge in a Grocery E-Commerce AI Shopping Assistant. Computer Journal, 4(2), 320-327. https://doi.org/10.58477/cj.v4i2.510
| DOI | https://doi.org/10.58477/cj.v4i2.510 |
| Publication Date | 2026-08-30 |
| Journal Section | Articles |
- Alavi, M., & Leidner, D. E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107–136. https://doi.org/10.2307/3250961
- Balakrishnan, J., & Dwivedi, Y. K. (2024). Conversational commerce: Entering the next stage of AI-powered digital assistants. Annals of Operations Research. https://doi.org/10.1007/s10479-021-04049-5
- Barnett, S., et al. (2024). Seven failure points when engineering a retrieval augmented generation system. In Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering – Software Engineering for AI (CAIN) (pp. 194–199). https://doi.org/10.1145/3644815.3644945
- Benita, K. (2024). Implementation of RAG in chatbot systems for enhanced real-time customer support in e-commerce. In Proceedings of the International Conference on Advanced Computing and Robotics Systems. IEEE. https://doi.org/10.1109/ICACRS62842.2024.10841586
- Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
- Chen, Y. (2025). Application of retrieval-augmented generation for interactive industrial knowledge management via a large language model. Computer Standards & Interfaces, 94, 103995. https://doi.org/10.1016/j.csi.2025.103995
- Desai, S., Yao, H., Porwal, U., & Lee, K. (2026). INSPIRE: Intent-aware neural sponsored product retrieval for e-commerce. In Proceedings of the ACM SIGIR Workshop on eCommerce (ECOM’26). arXiv:2606.23889
- Dong, X. L., et al. (2020). AutoKnow: Self-driving knowledge collection for products of thousands of types. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 2724–2734). https://doi.org/10.1145/3394486.3403323
- Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 532–550. https://doi.org/10.5465/amr.1989.4308385
- Eisenhardt, K. M., & Graebner, M. E. (2007). Theory building from cases: Opportunities and challenges. Academy of Management Journal, 50(1), 25–32. https://doi.org/10.5465/amj.2007.24160888
- Gioia, D. A., Corley, K. G., & Hamilton, A. L. (2013). Seeking qualitative rigor in inductive research: Notes on the Gioia methodology. Organizational Research Methods, 16(1), 15–31. https://doi.org/10.1177/1094428112452151
- Hogan, A., et al. (2021). Knowledge graphs. ACM Computing Surveys, 54(4), 1–37. https://doi.org/10.1145/3447772
- Jarrahi, M. H., et al. (2023). Artificial intelligence and knowledge management: A partnership between human and AI. Business Horizons, 66(1), 87–99. https://doi.org/10.1016/j.bushor.2022.03.002
- Klesel, M., & Wittmann, H. F. (2025). Retrieval-augmented generation (RAG). Business & Information Systems Engineering. https://doi.org/10.1007/s12599-025-00945-3
- Lewis, P., et al. (2020). Retrieval-augmented generation for knowledge-intensive NLP tasks. In Advances in Neural Information Processing Systems, 33 (pp. 9459–9474).
- Luo, X., et al. (2020). AliCoCo: Alibaba e-commerce cognitive concept net. In Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data (pp. 313–327). https://doi.org/10.1145/3318464.3386132
- Magnani, A., et al. (2022). Semantic retrieval at Walmart. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 3495–3503). https://doi.org/10.1145/3534678.3539164
- Myung, J., Park, J., & Han, J. (2025). HyST: LLM-powered hybrid retrieval over semi-structured tabular data. In Proceedings of the 2nd EARL Workshop on Evaluating and Applying Recommender Systems with LLMs. arXiv:2508.18048
- Ngai, E. W. T., et al. (2021). An intelligent knowledge-based chatbot for customer service. Electronic Commerce Research and Applications, 50, 101098. https://doi.org/10.1016/j.elerap.2021.101098
- Nickerson, R. C., Varshney, U., & Muntermann, J. (2013). A method for taxonomy development and its application in information systems. European Journal of Information Systems, 22(3), 336–359. https://doi.org/10.1057/ejis.2012.26
- Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. Oxford University Press.
- Nurmi, P., et al. (2008). Product retrieval for grocery stores. In Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 781–782). https://doi.org/10.1145/1390334.1390491
- Xiao, L., et al. (2021). End-to-end conversational search for online shopping with utterance transfer. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.emnlp-main.281
- Zhu, Y., Vedula, N., & Malmasi, S. (2025). Hint-augmented re-ranking: Efficient product search using LLM-based query decomposition. arXiv. https://arxiv.org/abs/2511.13994