Mind the Gap: A Dual Knowledge Graph Framework for Unified Multi-task User Intent Inference

Computer Science > Artificial Intelligence [Submitted on 7 Aug 2026] Mind the Gap: A Dual Knowledge Graph Framework for Unified Multi-task User Intent Inference Tzu-Cheng Peng (1), Chien Chin Chen (1), Chih-Hao Ku (2), Yung-Chun Chang (3) ((1) National Taiwan University, (2) University of North Texas, (3) Taipei Medical University) This paper proposes DKG-MTI, a dual knowledge graph framework for unified multi-task user intent inference from online travel reviews. Existing approaches often rely on hierarchical pipelines that suffer from error propagation or retrieval methods that ignore structural relationships in domain knowledge. To address these limitations, we introduce an inference-only knowledge augmentation framework that dynamically constructs a User-Specific Intent Knowledge Graph from each review and aligns it with a Global Hotel Knowledge Graph through structure-aware semantic smoothing. The aligned knowledge is combined with the original review and processed by a large language model to simultaneously predict aspect ratings and generate reverse user intent statements. Experiments on TripAdvisor reviews show that DKG-MTI consistently outperforms strong LLM and retrieval-based baselines in both classification and intent generation tasks, demonstrating the effectiveness of structure-aware knowledge alignment for scalable and explainable intent inference. Comments: Published in the PACIS 2026 Proceedings as a Completed Research Paper. AIS eLibrary: this https URL 17 pages, 5 figures Subjects: Artificial Intelligence (cs.AI); Computation and Language (cs.CL) Cite as: arXiv:2608.06752 [cs.AI]   (or arXiv:2608.06752v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2608.06752 Focus to learn more Journal reference: Proceedings of the Pacific Asia Conference on Information Systems (PACIS 2026), Paper 12, 2026 Submission history From: Chih Hao Ku [view email] [v1] Fri, 7 Aug 2026 03:18:13 UTC (1,205 KB) Access Paper: view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-08 Change to browse by: cs cs.CL References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)