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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 Cross-Model Consistency of Feature Importance in Electrospinning: Separating Robust from Model-Dependent Features LUCAS-MEGA: A Large-Scale Multimodal Dataset for Representation Learning in Soil-Environment Systems Inconsistent Databases and Argumentation Frameworks with Collective Attacks Workspace-Bench 1.0: Benchmarking AI Agents on Workspace Tasks with Large-Scale File Dependencies FINER-SQL: Boosting Small Language Models for Text-to-SQL Efficient Temporal Datalog Materialisation for Composite Event Recognition EGREFINE: An Execution-Grounded Optimization Framework for Text-to-SQL Schema Refinement Reliable Answers for Recurring Questions: Boosting Text-to-SQL Accuracy with Template Constrained Decoding FineState-Bench: Benchmarking State-Conditioned Grounding for Fine-grained GUI State Setting ObjectGraph: From Document Injection to Knowledge Traversal -- A Native File Format for the Agentic Era A Toolkit for Detecting Spurious Correlations in Speech Datasets SiriusHelper: An LLM Agent-Based Operations Assistant for Big Data Platforms Evergreen: Efficient Claim Verification for Semantic Aggregates CacheRAG: A Semantic Caching System for Retrieval-Augmented Generation in Knowledge Graph Question Answering Health System Scale Semantic Search Across Unstructured Clinical Notes Mining Negative Sequential Patterns to Improve Viral Genomic Feature Representation and Classification Prior-Aligned Data Cleaning for Tabular Foundation Models Spark Policy Toolkit: Semantic Contracts and Scalable Execution for Policy Learning in Spark Versioned Late Materialization for Ultra-Long Sequence Training in Recommendation Systems at Scale EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce How Hard is it to Decide if a Fact is Relevant to a Query? 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OLAP on Structurally Significant Data in Graphs
Kifayat Ullah Khan, Kamran Najeebullah, Waqas Nawaz, Young-Koo L · 2014-01-27 · via cs.DB updates on arXiv.org

Summarized data analysis of graphs using OLAP (Online Analytical Processing) is very popular these days. However due to high dimensionality and large size, it is not easy to decide which data should be aggregated for OLAP analysis. Though iceberg cubing is useful, but it is unaware of the significance of dimensional values with respect to the structure of the graph. In this paper, we propose a Structural Significance, SS, measure to identify the structurally significant dimensional values in each dimension. This leads to structure aware pruning. We then propose an algorithm, iGraphCubing, to compute the graph cube to analyze the structurally significant data using the proposed measure. We evaluated the proposed ideas on real and synthetic data sets and observed very encouraging results.

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