SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling
Abstract
1. Introduction
- We construct a semantic interaction graph USIG of user behaviors, use a self-attention mechanism to semantically analyze and model the aggregation of user interactions, and propose a new ranking optimization loss function to learn the similarity between user behaviors.
- We design a relation-aware aggregation module to extract multi-level semantic features from the knowledge graph and optimize the entity representation through the relation-aware attention mechanism.
- We introduce a higher-order relational path inference module to capture remote semantic dependencies for more accurate modeling of potential user preferences.
2. Related Work
2.1. Embedding-Based Methods
2.2. Path-Based Methods
2.3. Unified Methods
2.4. Compared to Our Work
3. A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm
3.1. Definition of the Problem
3.2. Model Structure
3.2.1. User Behavior Semantic Interaction Module
3.2.2. Relationship-Aware Aggregation Module
3.2.3. Higher-Order Relational Path Reasoning Module
4. Model Prediction
5. Experiment and Result Analysis
5.1. Dataset
5.2. Parameter Setting
5.3. Evaluation Index
5.4. Results and Analysis
5.4.1. Comparison Experiment
5.4.2. Model Efficiency Experiments
5.4.3. Cold-Start Effect Experiment
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Dataset | Amazon-Book | Last-FM |
---|---|---|
user | 70,679 | 23,566 |
item | 24,915 | 48,123 |
interactivity | 847,733 | 3,034,796 |
entity | 88,572 | 58,266 |
relation | 39 | 9 |
triad | 2,557,746 | 464,567 |
Experimental Configuration | Parameter |
---|---|
Python | 3.6.5 |
GPU | NVDIA RTX 4090 |
learning rate | 0.0001 |
dim | 64 |
batch_size | 1024 |
epoch | 200 |
context_hops | 3 |
node_dropout_rate | 0.5 |
Model | Amazon-Book | Last-FM | ||
---|---|---|---|---|
Recall@20 | NDCG@20 | Recall@20 | NDCG@20 | |
CKE | 0.1342 | 0.0698 | 0.0732 | 0.0630 |
KGAT | 0.1480 | 0.0801 | 0.0873 | 0.0743 |
KGCN | 0.1111 | 0.0569 | 0.0879 | 0.0694 |
CKAN | 0.1442 | 0.0698 | 0.0812 | 0.0660 |
KGCL | 0.1496 | 0.0793 | 0.0905 | 0.0769 |
KGRec | — | — | 0.0943 | 0.0810 |
SKGRec (ours) | 0.1702 | 0.0901 | 0.0943 | 0.0832 |
S′ Number | Amazon-Book | Last-FM | ||
---|---|---|---|---|
Recall@20 | NDCG@20 | Recall@20 | NDCG@20 | |
1 | 0.1574 | 0.0798 | 0.0859 | 0.0752 |
2 | 0.1607 | 0.0812 | 0.0872 | 0.0784 |
4 | 0.1658 | 0.0863 | 0.0905 | 0.0801 |
8 | 0.1695 | 0.0895 | 0.0937 | 0.0827 |
16 | 0.1702 | 0.0901 | 0.0943 | 0.0832 |
Model | Knowledge Graph Percentage | |||
---|---|---|---|---|
40% | 50% | 60% | 70% | |
KGAT | 0.0740 | 0.0765 | 0.0790 | 0.0815 |
KGCL | 0.0791 | 0.0822 | 0.0853 | 0.0870 |
KGRec | 0.0897 | 0.0909 | 0.0913 | 0.0925 |
SKGRec (ours) | 0.0907 | 0.0911 | 0.0922 | 0.0936 |
Recall Percentage | ||||
KGAT | 84.77% | 87.63% | 90.49% | 93.36% |
KGCL | 87.41% | 90.83% | 94.25% | 96.13% |
KGRec | 95.12% | 96.40% | 96.82% | 98.10% |
SKGRec (ours) | 96.18% | 96.61% | 97.77% | 99.26% |
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Xu, S.; Yang, Z.; Xu, J.; Feng, P. SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling. Computers 2025, 14, 288. https://doi.org/10.3390/computers14070288
Xu S, Yang Z, Xu J, Feng P. SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling. Computers. 2025; 14(7):288. https://doi.org/10.3390/computers14070288
Chicago/Turabian StyleXu, Siqi, Ziqian Yang, Jing Xu, and Ping Feng. 2025. "SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling" Computers 14, no. 7: 288. https://doi.org/10.3390/computers14070288
APA StyleXu, S., Yang, Z., Xu, J., & Feng, P. (2025). SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling. Computers, 14(7), 288. https://doi.org/10.3390/computers14070288