Uncertain Schema Matching
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Uncertain Schema Matching
Schema matching is the task of providing correspondences between concepts describing the meaning of data in various heterogeneous, distributed data sources. Schema matching is one of the basic operations required by the process of data and schema integration, and thus has a great effect on its outcomes, whether these involve targeted content delivery, view integration, database integration, query rewriting over heterogeneous sources, duplicate data elimination, or automatic streamlining of workflow activities that involve heterogeneous data sources. Although schema matching research has been ongoing for over 25 years, more recently a realization has emerged that schema matchers are inherently uncertain. Since 2003, work on the uncertainty in schema matching has picked up, along with research on uncertainty in other areas of data management. This lecture presents various aspects of uncertainty in schema matching within a single unified framework. We introduce basic formulations of uncertainty and provide several alternative representations of schema matching uncertainty. Then, we cover two common methods that have been proposed to deal with uncertainty in schema matching, namely ensembles, and top-K matchings, and analyze them in this context. We conclude with a set of real-world applications. Table of Contents: Introduction / Models of Uncertainty / Modeling Uncertain Schema Matching / Schema Matcher Ensembles / Top-K Schema Matchings / Applications / Conclusions and Future Work
Schema Matching and Mapping
Author: Zohra Bellahsene
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-02-14
Requiring heterogeneous information systems to cooperate and communicate has now become crucial, especially in application areas like e-business, Web-based mash-ups and the life sciences. Such cooperating systems have to automatically and efficiently match, exchange, transform and integrate large data sets from different sources and of different structure in order to enable seamless data exchange and transformation. The book edited by Bellahsene, Bonifati and Rahm provides an overview of the ways in which the schema and ontology matching and mapping tools have addressed the above requirements and points to the open technical challenges. The contributions from leading experts are structured into three parts: large-scale and knowledge-driven schema matching, quality-driven schema mapping and evolution, and evaluation and tuning of matching tasks. The authors describe the state of the art by discussing the latest achievements such as more effective methods for matching data, mapping transformation verification, adaptation to the context and size of the matching and mapping tasks, mapping-driven schema evolution and merging, and mapping evaluation and tuning. The overall result is a coherent, comprehensive picture of the field. With this book, the editors introduce graduate students and advanced professionals to this exciting field. For researchers, they provide an up-to-date source of reference about schema and ontology matching, schema and ontology evolution, and schema merging.
Search Computing
Author: Stefano Ceri
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-03-14
Search computing, which has evolved from service computing, focuses on building the answers to complex search queries by interacting with a constellation of cooperating search services, using the ranking and joining of results as the dominant factors for service composition. The field is multi-disciplinary in nature and takes advantage of contributions from other research areas such as knowledge representation, human-computer interfaces, psychology, sociology, economics, and legal sciences. This book, the second in the Search Computing series, describes the evolution of theories, technologies, and methods related to search computing. The book has been divided into eight parts, reflecting the main research directions within the Search Computing project. The parts focus on: search as an information exploration task; interaction design issues when dealing with multi-domain search results; modeling and semantic description of search services; the rank-join problem; query processing techniques and architectures; tools and mashups for application development; the application of search computing to bio-informatics; and the exploitation potentials of project results.