Neural Scalable Symbolic Search Framework for Complex Logical Queries with Multiple Free Variables
Weizhi Fei, Hang Yin, Zihao Wang, Shukai Zhao, Wei Zhang, Yangqiu Song
Read on arXiv →Key claim
NS3 improves joint ranking for complex queries in KGs.
The NS3 framework offers a novel approach to answering complex queries over knowledge graphs by approximating joint rankings without exhaustive enumeration. It improves joint ranking performance while maintaining strong accuracy on marginal queries. This advancement is particularly valuable for practitioners dealing with multi-variable queries in knowledge representation.
In plain English
The NS3 framework offers a novel approach to answering complex queries over knowledge graphs by approximating joint rankings without exhaustive enumeration. It improves joint ranking performance while maintaining strong accuracy on marginal queries. This advancement is particularly valuable for practitioners dealing with multi-variable queries in knowledge representation.
The proposed NS3 framework significantly advances the approach to joint ranking in complex query answering over knowledge graphs.
The paper provides strong experimental results across multiple datasets and releases code for reproducibility.
Deep reliability assessment
The methodology supports improved joint ranking for EFOk queries through a budgeted framework, but it may overclaim effectiveness by not addressing all complexities of larger k-variable queries. The results are promising but may not generalize across all types of knowledge graphs or query structures.
Reproducibility
Yes, the source code is provided at https://github.com/HKUST-KnowComp/NS3_KDD2026.
Discussion questions
- 1.What assumptions about the completeness of knowledge graphs underlie the effectiveness of the proposed method?
- 2.How can the findings be applied to real-world applications in industries like finance or security?
- 3.What would happen if the knowledge graph had a significantly higher degree of incompleteness than tested?
Key figure
Figure 1 visualizes an EFO2 query related to fraudulent activities, showing its logical formula and query graph structure.