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Dirty data

Dirty data is inaccurate, incomplete or erroneous data, especially in a computer system or database. In reference to databases, this is data that… Expand
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2014
Highly Cited
2014
It is widely accepted that proper data publishing is difficult. The majority of Linked Open Data (LOD) does not meet even a core… Expand
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Highly Cited
2014
Highly Cited
2014
In emerging Big Data scenarios, obtaining timely, high-quality answers to aggregate queries is difficult due to the challenges of… Expand
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Highly Cited
2013
Highly Cited
2013
Internet of Things (IoT) will comprise billions of devices that can sense, communicate, compute and potentially actuate. Data… Expand
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Highly Cited
2013
Highly Cited
2013
Despite the increasing importance of data quality and the rich theoretical and practical contributions in all aspects of data… Expand
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2013
2013
This paper introduces a new approach for conflict resolution: given a set of tuples pertaining to the same entity, it is to… Expand
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Highly Cited
2012
Highly Cited
2012
Data quality is a vital topic for business analytics in order to gain accurate insight and make correct decisions in many data… Expand
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Highly Cited
2010
Highly Cited
2010
We consider multi-task learning in the setting of multiple linear regression, and where some relevant features could be shared… Expand
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Highly Cited
2009
Highly Cited
2009
Memory scaling is in jeopardy as charge storage and sensing mechanisms become less reliable for prevalent memory technologies… Expand
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Highly Cited
2003
Highly Cited
2003
Today large corporations are constructing enterprise data warehouses from disparate data sources in order to run enterprise-wide… Expand
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Highly Cited
2000
Highly Cited
2000
This paper introduces column caching, a exible mechanism that allows software to dynamically customize cache behavior through ne… Expand
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