Text and structured data fusion in data tamer at scale

Author(s)
Gubanov, Michael; Stonebraker, Michael; Bruckner, Daniel
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Abstract
Large-scale text data research has recently started to regain momentum [1]-[10], because of the wealth of up to date information communicated in unstructured format. For example, new information in online media (e.g. Web blogs, Twitter, Facebook, news feeds, etc) becomes instantly available and is refreshed regularly, has very broad coverage and other valuable properties unusual for other data sources and formats. Therefore, many enterprises and individuals are interested in integrating and using unstructured text in addition to their structured data.
Date issued
2014-03
URI
http://hdl.handle.net/1721.1/90856
Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
2014 IEEE 30th International Conference on Data Engineering (ICDE)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Gubanov, Michael, Michael Stonebraker, and Daniel Bruckner. “Text and Structured Data Fusion in Data Tamer at Scale.” 2014 IEEE 30th International Conference on Data Engineering, ICDE (March 31-April 4, 2014), Chicago, IL. IEEE. p.1258-1261.
Version: Author's final manuscript
Other identifiers
INSPEC Accession Number: 14319242
ISBN
978-1-4799-2555-1
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