activity
20062026
most citedThe Future is Big Graphs! A Community View on Graph Processing Systems

157 citations · 300 across the 43 of their papers we have counts for

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Showing 2017 · cs.DBShow all

5 papers · 2 filters

cs.DB2017★ 2 cited

Human-Centric Data Cleaning [Vision]

El Kindi Rezig, Mourad Ouzzani, Ahmed K. Elmagarmid +1

Data Cleaning refers to the process of detecting and fixing errors in the data. Human involvement is instrumental at several stages of this process, e.g., to identify and repair er…

cs.DB2017★ 1 cited

Pattern-Driven Data Cleaning

El Kindi Rezig, Mourad Ouzzani, Walid G. Aref +2

Data is inherently dirty and there has been a sustained effort to come up with different approaches to clean it. A large class of data repair algorithms rely on data-quality rules…

cs.DB2017★ 2 cited

Empowering In-Memory Relational Database Engines with Native Graph Processing

Mohamed S. Hassan, Tatiana Kuznetsova, Hyun Chai Jeong +2

The plethora of graphs and relational data give rise to many interesting graph-relational queries in various domains, e.g., finding related proteins satisfying relational predicate…

cs.DB2017★ 4 cited

FAST: Frequency-Aware Spatio-Textual Indexing for In-Memory Continuous Filter Query Processing

Ahmed R. Mahmood, Ahmed M. Aly, Walid G. Aref

Many applications need to process massive streams of spatio-textual data in real-time against continuous spatio-textual queries. For example, in location-aware ad targeting publish…

cs.DB2017

SBG-Sketch: A Self-Balanced Sketch for Labeled-Graph Stream Summarization

Mohamed S. Hassan, Bruno Ribeiro, Walid G. Aref

Applications in various domains rely on processing graph streams, e.g., communication logs of a cloud-troubleshooting system, road-network traffic updates, and interactions on a so…