An Architecture for Indexing and Querying Dataspaces. Vol.2
Finding Associations Among Data Sources on the Web
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The huge amount of information published on the Web gave birth to dataspaces, collections of inter-connected (and sometimes structured) information sources created by autonomous users. The existence of dataspaces opens room for a new kind of research, with the purpose of providing meaningful access to data, regardless of its content and format, as long as it is available. The author proposes a novel approach to query dataspaces, based on an architecture that decomposes data as sets of records and stores it in optimized index structures. In this book, the author presents an extension of the pro...
The huge amount of information published on the Web gave birth to dataspaces, collections of inter-connected (and sometimes structured) information sources created by autonomous users. The existence of dataspaces opens room for a new kind of research, with the purpose of providing meaningful access to data, regardless of its content and format, as long as it is available. The author proposes a novel approach to query dataspaces, based on an architecture that decomposes data as sets of records and stores it in optimized index structures. In this book, the author presents an extension of the proposed framework that is able to answer user queries by correlating information from disparate data sources. To demonstrate the viability of the method, experiments analyze the performance of the rewriting algorithms used to answers queries. The underlying indexes are also analyzed with respect to existing approaches that address the problem in a different way. For those that are willing to explore the world of information integration, it is worth taking a look inside this book.
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