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Columbia's Snowball and QXtract Projects

Snowball and QXtract: Scalable Information Extraction over Large Document Collections. Text documents (e.g., newspaper articles) often contain valuable structured data that is hidden in regular English sentences. For many applications, this data is best exploited if available as a relational table that could be used to answer precise queries or to run data mining tasks. Receives as input an arbitrary information extraction system, together with a handful of training tuples. QXtract. Modeling Query-Based ...

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Columbia's Snowball and QXtract Projects | snowball.cs.columbia.edu Reviews
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Snowball and QXtract: Scalable Information Extraction over Large Document Collections. Text documents (e.g., newspaper articles) often contain valuable structured data that is hidden in regular English sentences. For many applications, this data is best exploited if available as a relational table that could be used to answer precise queries or to run data mining tasks. Receives as input an arbitrary information extraction system, together with a handful of training tuples. QXtract. Modeling Query-Based ...
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1 snowball
2 dmkd'00 paper
3 sigmod'01 demo
4 ismb'03 paper
5 qxtract
6 sigmod'03 demo
7 people
8 eugene agichtein
9 luis gravano
10 mayer crystal
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Columbia's Snowball and QXtract Projects | snowball.cs.columbia.edu Reviews

https://snowball.cs.columbia.edu

Snowball and QXtract: Scalable Information Extraction over Large Document Collections. Text documents (e.g., newspaper articles) often contain valuable structured data that is hidden in regular English sentences. For many applications, this data is best exploited if available as a relational table that could be used to answer precise queries or to run data mining tasks. Receives as input an arbitrary information extraction system, together with a handful of training tuples. QXtract. Modeling Query-Based ...

LINKS TO THIS WEBSITE

cudbg.github.io cudbg.github.io

Projects :: Database Research Group :: Columbia University

http://cudbg.github.io/projects.html

Information Extraction at Columbia. Event Identification in Social Media. Database Algorithms for Modern CPU Memory Hierarchies. DPU: Database Processing Unit. Database Processing on GPUs. Data Visualization Management Systems. Data Exploration and Explanation. Data Cleaning for Data Science. Database Parallelism on Multicore Machines. Rapid Updates and Snapshot-Based Queries Using Multicore Processors. The Columbia Fast Query Project. Romanesque Architecture of the Bourbonnais: Tools for Discovery.

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Columbia's Snowball and QXtract Projects

Snowball and QXtract: Scalable Information Extraction over Large Document Collections. Text documents (e.g., newspaper articles) often contain valuable structured data that is hidden in regular English sentences. For many applications, this data is best exploited if available as a relational table that could be used to answer precise queries or to run data mining tasks. Receives as input an arbitrary information extraction system, together with a handful of training tuples. QXtract. Modeling Query-Based ...

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