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

D
Docker
U
Unit 42
Google DeepMind News
Google DeepMind News
B
Blog RSS Feed
S
SegmentFault 最新的问题
阮一峰的网络日志
阮一峰的网络日志
雷峰网
雷峰网
Microsoft Security Blog
Microsoft Security Blog
爱范儿
爱范儿
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
博客园_首页
Apple Machine Learning Research
Apple Machine Learning Research
罗磊的独立博客
GbyAI
GbyAI
Stack Overflow Blog
Stack Overflow Blog
Martin Fowler
Martin Fowler
宝玉的分享
宝玉的分享
L
LangChain Blog
Engineering at Meta
Engineering at Meta
量子位
有赞技术团队
有赞技术团队
博客园 - 【当耐特】
A
About on SuperTechFans
Y
Y Combinator 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
Star Pattern Fragments: Accessing Knowledge Graphs throug...
Christian Aebeloe, Ilkcan Keles, Gabriela Montoya, Katja Hose · 2020-02-21 · via cs.DB updates on arXiv.org

The Semantic Web offers access to a vast Web of interlinked information accessible via SPARQL endpoints. Such endpoints offer a well-defined interface to retrieve results for complex SPARQL queries. The computational load for processing such SPARQL endpoints offer access to a vast amount of interlinked information. While they offer a well-defined interface for efficiently retrieving results for complex SPARQL queries, complex query loads can easily overload or crash endpoints as all the computational load of answering the queries resides entirely with the server hosting the endpoint. Recently proposed interfaces, such as Triple Pattern Fragments, have therefore shifted some of the query processing load from the server to the client at the expense of increased network traffic in the case of non-selective triple patterns. This paper therefore proposes Star Pattern Fragments (SPF), an RDF interface enabling a better load balancing between server and client by decomposing SPARQL queries into star-shaped subqueries, evaluating them on the server side. Experiments using synthetic data (WatDiv), as well as real data (DBpedia), show that SPF does not only significantly reduce network traffic, it is also up to two orders of magnitude faster than the state-of-the-art interfaces under high query load.