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Recent years have witnessed a proliferation of large-scale knowledge bases, including Wikipedia, Freebase, YAGO, Microsoft's Satori, and Google's Knowledge Graph. To increase the scale even further, we need to explore automatic methods for constructing knowledge bases. Previous approaches have primarily focused on text-based extraction, which can be very(More)
Reference reconciliation is the problem of identifying when different references (i.e., sets of attribute values) in a dataset correspond to the same real-world entity. Most previous literature assumed references to a <i>single</i> class that had a fair number of attributes (e.g., research publications). We consider complex information spaces: our(More)
Many data management applications, such as setting up Web portals, managing enterprise data, managing community data, and sharing scientific data, require integrating data from multiple sources. Each of these sources provides a set of values and different sources can often provide conflicting values. To present quality data to users, it is critical that(More)
This paper reports our first set of results on managing uncertainty in data integration. We posit that data-integration systems need to handle uncertainty at three levels and do so in a principled fashion. First, the semantic mappings between the data sources and the mediated schema may be approximate because there may be too many of them to be created and(More)
Data integration systems offer a uniform interface to a set of data sources. Despite recent progress, setting up and maintaining a data integration application still requires significant upfront effort of creating a mediated schema and semantic mappings from the data sources to the mediated schema. Many application contexts involving multiple data sources(More)
Dataspaces are collections of heterogeneous and partially unstructured data. Unlike data-integration systems that also offer uniform access to heterogeneous data sources, dataspaces do not assume that all the semantic relationships between sources are known and specified. Much of the user interaction with dataspaces involves exploring the data, and users do(More)
The World Wide Web is witnessing an increase in the amount of structured content – vast heterogeneous collections of structured data are on the rise due to the Deep Web, annotation schemes like Flickr, and sites like Google Base. While this phenomenon is creating an opportunity for structured data management, dealing with heterogeneity on the web-scale(More)
Modern information management applications often require integrating data from a variety of data sources, some of which may copy or buy data from other sources. When these data sources model a dynamically changing world (e.g., people’s contact information changes over time, restaurants open and go out of business), sources often provide out-of-date data.(More)