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

WordPress大学
WordPress大学
G
Google Developers Blog
M
MIT News - Artificial intelligence
Vercel News
Vercel News
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
GbyAI
GbyAI
B
Blog RSS Feed
Blog — PlanetScale
Blog — PlanetScale
Microsoft Security Blog
Microsoft Security Blog
V
Visual Studio Blog
Stack Overflow Blog
Stack Overflow Blog
雷峰网
雷峰网
The Cloudflare Blog
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
F
Fortinet All Blogs
L
LangChain Blog
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
A
About on SuperTechFans
T
The Blog of Author Tim Ferriss
B
Blog
J
Java Code Geeks
Hugging Face - Blog
Hugging Face - Blog
I
InfoQ
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

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
Coherence of linear and surface data: Methodological prop...
2022-09-15 · via cs.DB updates on arXiv.org

The real world and its geographic objects are modeled and represented in different spatial databases. Each of these databases provides only a partial description (in space and time) of the geographic objects represented. Sometimes, producers and users of databases need to connect several of them for updates or comparisons. Much of the work in spatial database management focuses on matching these spatial databases and more particularly network databases, such as road networks. With regard to network data, one situation remains neglected, that of matching a linear database (with polylines objects) with a surface database (with polygons objects). In any case, users also need to connect these two types of spatial database. In this paper, a case study is made using French examples (Cachan, near Paris), as well as international case studies (Bordeaux in France, Victoria in Canada, and Copenhagen in Denmark), to propose an approach intended to make coherent network geographical objects in two different reference frames (linear and surface). This issue is addressed here through the example of road data. The surface data are then formalized in order to adapt them to linear data describing the same geographical objects. In the end, a polygon in the surface data corresponds to a single polyline in the linear data. This consistency should simplify the transfer of information from one reference frame (linear or surface) to the other. In other words, the methodology developed aims to make linear and surfacegeographic data interoperable.