13 citations · 30 across the 14 of their papers we have counts for
14 papers
BI-Agent and BI-Bench: Towards Automating End-to-End Business Intelligence
Chuxuan Hu, Yeye He, Penny Zhou +3
Business intelligence (BI) is a cornerstone of enterprise decision-making and is widely used by enterprise users in software such as Power BI and Tableau. In traditional BI workflo…
Auto-Relate: A Unified Approach to Discovering Reliable Functional Relationships Leveraging Statistical Tests
Ziyan Han, Yeye He, Shuyuan Kang +8
Tables in spreadsheets, computational notebooks, and databases often contain rich inter-column relationships. Yet these relationships are typically implicit and are often lost when…
Nexus: Inferring Join Graphs from Metadata Alone via Iterative Low-Rank Matrix Completion
Tianji Cong, Yuanyuan Tian, Andreas Mueller +5
Automatically inferring join relationships is a critical task for effective data discovery, integration, querying and reuse. However, accurately and efficiently identifying these r…
Auto-Tables: Synthesizing Multi-Step Transformations to Relationalize Tables without Using Examples
Peng Li, Yeye He, Cong Yan +2
Relational tables, where each row corresponds to an entity and each column corresponds to an attribute, have been the standard for tables in relational databases. However, such a s…
Auto-BI: Automatically Build BI-Models Leveraging Local Join Prediction and Global Schema Graph
Yiming Lin, Yeye He, Surajit Chaudhuri
Business Intelligence (BI) is crucial in modern enterprises and billion-dollar business. Traditionally, technical experts like database administrators would manually prepare BI-mod…
Auto-Validate by-History: Auto-Program Data Quality Constraints to Validate Recurring Data Pipelines
Dezhan Tu, Yeye He, Weiwei Cui +5
Data pipelines are widely employed in modern enterprises to power a variety of Machine-Learning (ML) and Business-Intelligence (BI) applications. Crucially, these pipelines are \em…
Ground Truth Inference for Weakly Supervised Entity Matching
Renzhi Wu, Alexander Bendeck, Xu Chu +1
Entity matching (EM) refers to the problem of identifying pairs of data records in one or more relational tables that refer to the same entity in the real world. Supervised machine…
Auto-Tag: Tagging-Data-By-Example in Data Lakes
Yeye He, Jie Song, Yue Wang +5
As data lakes become increasingly popular in large enterprises today, there is a growing need to tag or classify data assets (e.g., files and databases) in data lakes with addition…
Auto-Pipeline: Synthesizing Complex Data Pipelines By-Target Using Reinforcement Learning and Search
Junwen Yang, Yeye He, Surajit Chaudhuri
Recent work has made significant progress in helping users to automate single data preparation steps, such as string-transformations and table-manipulation operators (e.g., Join, G…
Demonstration of Panda: A Weakly Supervised Entity Matching System
Renzhi Wu, Prem Sakala, Peng Li +2
Entity matching (EM) refers to the problem of identifying tuple pairs in one or more relations that refer to the same real world entities. Supervised machine learning (ML) approach…
Auto-Validate: Unsupervised Data Validation Using Data-Domain Patterns Inferred from Data Lakes
Jie Song, Yeye He
Complex data pipelines are increasingly common in diverse applications such as BI reporting and ML modeling. These pipelines often recur regularly (e.g., daily or weekly), as BI re…
Auto-FuzzyJoin: Auto-Program Fuzzy Similarity Joins Without Labeled Examples
Peng Li, Xiang Cheng, Xu Chu +2
Fuzzy similarity join is an important database operator widely used in practice. So far the research community has focused exclusively on optimizing fuzzy join \textit{scalability}…
Synthesizing Mapping Relationships Using Table Corpus
Yue Wang, Yeye He
Mapping relationships, such as (country, country-code) or (company, stock-ticker), are versatile data assets for an array of applications in data cleaning and data integration like…
On Load Shedding in Complex Event Processing
Yeye He, Siddharth Barman, Jeffrey F. Naughton
Complex Event Processing (CEP) is a stream processing model that focuses on detecting event patterns in continuous event streams. While the CEP model has gained popularity in the r…