惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Martin Fowler
Martin Fowler
WordPress大学
WordPress大学
月光博客
月光博客
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
大猫的无限游戏
大猫的无限游戏
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
博客园 - 聂微东
Apple Machine Learning Research
Apple Machine Learning Research
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
雷峰网
雷峰网
小众软件
小众软件
酷 壳 – CoolShell
酷 壳 – CoolShell
博客园 - 叶小钗
美团技术团队
宝玉的分享
宝玉的分享
Hugging Face - Blog
Hugging Face - Blog
阮一峰的网络日志
阮一峰的网络日志
A
About on SuperTechFans
Jina AI
Jina AI
D
Docker
Last Week in AI
Last Week in AI
MongoDB | Blog
MongoDB | Blog
Stack Overflow Blog
Stack Overflow Blog
Microsoft Azure Blog
Microsoft Azure Blog

cs.DB updates on arXiv.org

Block-Sphere Vector Quantization GroupAffect-4: A Multimodal Dataset of Four-Person Collaborative Interaction CogScale: Scalable Benchmark for Sequence Processing TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards LogRouter: Adaptive Two-Level LLM Routing for Log Question Answering in Big Data Systems Agentic Cost-Aware Query Planning with Knowledge Distillation for Big Data Analytics Covariance Structure and Coordinate Heterogeneity Govern Binary Quantization of Contrastive Embeddings IVF-TQ: Calibration-Free Streaming Vector Search via a Codebook-Free Residual Layer Automatic Unsupervised Ensemble Outlier Model Selection--Extended Version A Generative AI Framework for Intelligent Utility Billing CO 2 Analytics and Sustainable Resource Optimisation Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks Gaussian Relational Graph Transformer Croissant Baker: Metadata Generation for Discoverable, Governable, and Reusable ML Datasets Reducing Hallucination in Vision-Language Models via Stage-wise Preference Optimization under Distribution Shift A Horn extension of DL-Lite with NL data complexity 3D Primitives are a Spatial Language for VLMs Enabling AI-Native Mobility in 6G: A Real-World Dataset for Handover, Beam Management, and Timing Advance A CAP-like Trilemma for Large Language Models: Correctness, Non-bias, and Utility under Semantic Underdetermination EpiCastBench: Datasets and Benchmarks for Multivariate Epidemic Forecasting FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models Toward Multi-Database Query Reasoning for Text2Cypher Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities Detect, Localize, and Explain: Interactive Hierarchical Log Anomaly Analytics with LLM Augmentation Open Ontologies: Tool-Augmented Ontology Engineering with Stable Matching Alignment Machine Learning-Based Pre-Test Risk Stratification for PCR-Confirmed Chlamydia Using Patient-Reported Data and Urine Biomarkers Reconciling Consistency-Based Diagnosis with Actual-Causality-Based Explanations PrepBench: How Far Are We from Natural-Language-Driven Data Preparation? Anatomy of a Query: W5H Dimensions and FAR Patterns for Text-to-SQL Evaluation Building informative materials datasets beyond targeted objectives
Designing and Comparing RPQ Semantics
Victor Marsault, Antoine Meyer · 2026-02-12 · via cs.DB updates on arXiv.org

Modern property graph database query languages such as Cypher, PGQL, GSQL, and the standard GQL draw inspiration from the formalism of regular path queries (RPQs). In order to output walks explicitly, they depart from the classical and well-studied homomorphism semantics. However, it then becomes difficult to present results to users because RPQs may match infinitely many walks. The aforementioned languages use ad-hoc criteria to select a finite subset of those matches. For instance, Cypher uses trail semantics, discarding walks with repeated edges; PGQL and GSQL use shortest walk semantics, retaining only the walks of minimal length among all matched walks; and GQL allows users to choose from several semantics. Even though there is academic research on these semantics, it focuses almost exclusively on evaluation efficiency. In an attempt to better understand, choose and design RPQ semantics, we present a framework to categorize and compare them according to other criteria. We formalize several possible properties, pertaining to the study of RPQ semantics seen as mathematical functions mapping a database and a query to a finite set of walks. We show that some properties are mutually exclusive, or cannot be met. We also give several new RPQ semantics as examples. Some of them may provide ideas for the design of new semantics for future graph database query languages.