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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 Data Integration through Smart Copy & Paste
2009-09-10 · via cs.DB updates on arXiv.org

In many scenarios, such as emergency response or ad hoc collaboration, it is critical to reduce the overhead in integrating data. Ideally, one could perform the entire process interactively under one unified interface: defining extractors and wrappers for sources, creating a mediated schema, and adding schema mappings ? while seeing how these impact the integrated view of the data, and refining the design accordingly. We propose a novel smart copy and paste (SCP) model and architecture for seamlessly combining the design-time and run-time aspects of data integration, and we describe an initial prototype, the CopyCat system. In CopyCat, the user does not need special tools for the different stages of integration: instead, the system watches as the user copies data from applications (including the Web browser) and pastes them into CopyCat?s spreadsheet-like workspace. CopyCat generalizes these actions and presents proposed auto-completions, each with an explanation in the form of provenance. The user provides feedback on these suggestions ? through either direct interactions or further copy-and-paste operations ? and the system learns from this feedback. This paper provides an overview of our prototype system, and identifies key research challenges in achieving SCP in its full generality.