Databases constructed automatically through web mining and information extraction often overlap with databases constructed and curated by hand. These two types of databases are complementary: automatic extraction provides increased scope, while curated databases provide increased accuracy. The uncertain nature of such integration tasks suggests that the final representation of the merged database should represent multiple possible values. We present initial work on a system to integrate two bibliographic databases, DBLP and Rexa, while maintaining and assigning probabilistic confidences to different alternative values in merged records
One of the problems in data integration is data overlap: the fact that different data sources have d...
Data interoperability is a major issue in data management for data science and big data analytics. P...
Abstract — One of the problems in data integration is data overlap: the fact that different data sou...
Abstract — Collected data often contains uncertainties. Prob-abilistic databases have been proposed ...
At present, many information sources are available wherever you are. Most of the time, the informati...
Probabilistic data integration is a specific kind of data integration where integration problems suc...
In previous work, we have introduced probabilistic description logic programs for the Semantic Web, ...
In data integration we transform information from a source into a target schema. A general problem i...
Real world applications that deal with information extraction, such as business intelligence softwar...
Probabilistic description logic programs are a powerful tool for knowledge representation in the Sem...
Abstract. There is a large amount of data that is published on the Web and several techniques have b...
The integration of both distributed schemas and data repositories is a major challenge in data and k...
This paper proposes a method for the automatic discovery of probabilistic relationships in the envir...
A bioinformatician has a large number of homology data sources to choose from. These data sources ne...
Over the recent past, information extraction (IE) systems such as Nell and ReVerb have attained much...
One of the problems in data integration is data overlap: the fact that different data sources have d...
Data interoperability is a major issue in data management for data science and big data analytics. P...
Abstract — One of the problems in data integration is data overlap: the fact that different data sou...
Abstract — Collected data often contains uncertainties. Prob-abilistic databases have been proposed ...
At present, many information sources are available wherever you are. Most of the time, the informati...
Probabilistic data integration is a specific kind of data integration where integration problems suc...
In previous work, we have introduced probabilistic description logic programs for the Semantic Web, ...
In data integration we transform information from a source into a target schema. A general problem i...
Real world applications that deal with information extraction, such as business intelligence softwar...
Probabilistic description logic programs are a powerful tool for knowledge representation in the Sem...
Abstract. There is a large amount of data that is published on the Web and several techniques have b...
The integration of both distributed schemas and data repositories is a major challenge in data and k...
This paper proposes a method for the automatic discovery of probabilistic relationships in the envir...
A bioinformatician has a large number of homology data sources to choose from. These data sources ne...
Over the recent past, information extraction (IE) systems such as Nell and ReVerb have attained much...
One of the problems in data integration is data overlap: the fact that different data sources have d...
Data interoperability is a major issue in data management for data science and big data analytics. P...
Abstract — One of the problems in data integration is data overlap: the fact that different data sou...