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Eugene Wu
Researcher at Columbia University
Publications - 125
Citations - 5781
Eugene Wu is an academic researcher from Columbia University. The author has contributed to research in topics: Computer science & Visualization. The author has an hindex of 32, co-authored 105 publications receiving 5266 citations. Previous affiliations of Eugene Wu include Massachusetts Institute of Technology & Simon Fraser University.
Papers
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Proceedings ArticleDOI
High-performance complex event processing over streams
TL;DR: This paper proposes a complex event language that significantly extends existing event languages to meet the needs of a range of RFID-enabled monitoring applications and describes a query plan-based approach to efficiently implementing this language.
Journal ArticleDOI
WebTables: exploring the power of tables on the web
TL;DR: The WEBTABLES system develops new techniques for keyword search over a corpus of tables, and shows that they can achieve substantially higher relevance than solutions based on a traditional search engine.
Relational Cloud: A Database-as-a-Service for the Cloud
Carlo Curino,Evan P. C. Jones,Raluca Ada Popa,Nirmesh Malviya,Eugene Wu,Samuel Madden,Hari Balakrishnan,Nickolai Zeldovich +7 more
TL;DR: Relational Cloud as discussed by the authors is a transactional database-as-a-service (DBaaS) system that uses a graph-based data partitioning algorithm to achieve near-linear elastic scalability.
Posted Content
Human-powered Sorts and Joins
TL;DR: The authors integrated crowds into a declarative workflow engine called Qurk to reduce the burden on workflow designers and used humans to compare items for sorting and joining data, two of the most common operations in DBMSs.
Journal ArticleDOI
Human-powered sorts and joins
TL;DR: This paper describes how MTurk tasks for processing datasets with humans are currently designed with significant reimplementation of common workflows and ad-hoc selection of parameters such as price to pay per task, and proposes a number of optimizations, including task batching, replacing pairwise comparisons with numerical ratings, and pre-filtering tables before joining them.