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

雷峰网
雷峰网
Y
Y Combinator Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
The Cloudflare Blog
博客园_首页
J
Java Code Geeks
A
About on SuperTechFans
人人都是产品经理
人人都是产品经理
量子位
C
Check Point Blog
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
博客园 - 三生石上(FineUI控件)
L
LangChain Blog
N
Netflix TechBlog - Medium
Hugging Face - Blog
Hugging Face - Blog
B
Blog
美团技术团队
Microsoft Security Blog
Microsoft Security Blog
P
Proofpoint News Feed
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
宝玉的分享
宝玉的分享
罗磊的独立博客
MongoDB | Blog
MongoDB | Blog
Last Week in AI
Last Week in AI

cs.HC updates on arXiv.org

Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video Vision-Language Models Suppress Female Representations Under Ambiguous Input The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace TUX: Measuring Human--AI Tacit Understanding LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality Analyzing Persona Effects in Generated Explanations from Multimodal LLM Agents in Urban Perception First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering The Timing Dependencies of Trust: Speed, Accuracy, and cBCI Neuro-Decoupling in Human-AI Teams Bayesian Distributional Models of Executive Functioning Visual Matters: Connecting Aesthetic Appeal and Production Quality of Photos, Infographics and Data Visualizations to Credibility of Social Media Posts Data-driven Head Motion Generation through Natural Gaze-Head Coordination Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why Perceptually Lossless Tactile Texture Synthesis with Compact Spectral Envelope Models MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data CogAdapt: Transferring Clinical ECG Foundation Models to Wearable Cognitive Load Assessment via Lead Adaptation Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build PaintCopilot: Modeling Painting as Autonomous Artistic Continuation Personality Engineering with AI Agents: A New Methodology for Negotiation Research PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education Conversations in Space: Structuring Non-Linear LLM Interactions on a Canvas MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis nASR: An End-to-End Trainable Neural Layer for Channel-Level EEG Artifact Subspace Reconstruction in Real-Time BCI
Sigma Worksheet: Interactive Construction of OLAP Queries
James Gale, Max Seiden, Gretchen Atwood, Jason Frantz, Rob Wooll · 2020-12-02 · via cs.HC updates on arXiv.org

The new generation of cloud data warehouses (CDWs) brings large amounts of data and compute power closer to users in enterprises. The ability to directly access the warehouse data, interactively analyze and explore it at scale can empower users to improve their decision making cycles. However, existing tools for analyzing data in CDWs are either limited in ad-hoc transformations or difficult to use for business users, the largest user segment in enterprises. Here we introduce Sigma Worksheet, a new interactive system that enables users to easily perform ad-hoc visual analysis of data in CDWs at scale. For this, Sigma Worksheet provides an accessible spreadsheet-like interface for data analysis through direct manipulation. Sigma Worksheet dynamically constructs matching SQL queries from user interactions on this familiar interface, building on the versatility and expressivity of SQL. Sigma Worksheet executes constructed queries directly on CDWs, leveraging the superior characteristics of the new generation CDWs, including scalability. To evaluate Sigma Worksheet, we first demonstrate its expressivity through two real life use cases, cohort analysis and sessionization. We then measure the performance of the Worksheet generated queries with a set of experiments using the TPC-H benchmark. Results show the performance of our compiled SQL queries is comparable to that of the reference queries of the benchmark. Finally, to assess the usefulness of Sigma Worksheet in deployment, we elicit feedback through a 100-person survey followed by a semi-structured interview study with 70 participants. We find that Sigma Worksheet is easier to use and learn, improving the productivity of users. Our findings also suggest Sigma Worksheet can further improve user experience by providing guidance to users at various steps of data analysis.