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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
Interactive in-base street model edit: how common GIS sof...
Remi Cura, Julien Perret, Nicolas Paparoditis · 2018-01-18 · via cs.DB updates on arXiv.org

Our modern world produces an increasing quantity of data, and especially geospatial data, with advance of sensing technologies, and growing complexity and organisation of vector data. Tools are needed to efficiently create and edit those vector geospatial data. Procedural generation has been a tool of choice to generate strongly organised data, yet it may be hard to control. Because those data may be involved to take consequence-full real life decisions, user interactions are required to check data and edit it. The classical process to do so would be to build an adhoc Graphical User Interface (GUI) tool adapted for the model and method being used. This task is difficult, takes a large amount of resources, and is very specific to one model, making it hard to share and re-use. Besides, many common generic GUI already exists to edit vector data, each having its specialities. We propose a change of paradigm; instead of building a specific tool for one task, we use common GIS software as GUIs, and deport the specific interactions from the software to within the database. In this paradigm, GIS software simply modify geometry and attributes of database layers, and those changes are used by the database to perform automated task. This new paradigm has many advantages. The first one is genericity. With in-base interaction, any GIS software can be used to perform edition, whatever the software is a Desktop sofware or a web application. The second is concurrency and coherency. Because interaction is in-base, use of database features allows seamless multi-user work, and can guarantee that the data is in a coherent state. Last we propose tools to facilitate multi-user edits, both during the edit phase (each user knows what areas are edited by other users), and before and after edit (planning of edit, analyse of edited areas).