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Author: Avigdor Gal
Publisher: Springer Nature
ISBN: 3031018451
Category : Computers
Languages : en
Pages : 85
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Book Description
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
Author: Avigdor Gal
Publisher: Springer Nature
ISBN: 3031018451
Category : Computers
Languages : en
Pages : 85
Get Book Here
Book Description
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
Author: Zohra Bellahsene
Publisher: Springer Science & Business Media
ISBN: 3642165184
Category : Computers
Languages : en
Pages : 326
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Book Description
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.
Author: Avigdor Gal
Publisher: Morgan & Claypool
ISBN: 9781608453931
Category : Mathematics
Languages : en
Pages : 100
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Book Description
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. 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. Schema matching research has been going on for more than 25 years. Over the years, a significant body of work has been devoted to the identification of schema matchers, heuristics for schema matching. The main objective of schema matchers is to provide correspondences that will be effective from the user's point of view. Over the years, 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.
Author: Henri Prade
Publisher: Springer Science & Business Media
ISBN: 3540754075
Category : Business & Economics
Languages : en
Pages : 286
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Book Description
This book constitutes the refereed proceedings of the First International Conference on Scalable Uncertainty Management, SUM 2007, held in Washington, DC, USA, in October 2007. The 20 revised full papers presented were carefully reviewed and selected from numerous submissions for inclusion in the book. The papers address artificial intelligence researchers, database researchers and practitioners.
Author: Stefano Ceri
Publisher: Springer Science & Business Media
ISBN: 3642196675
Category : Computers
Languages : en
Pages : 272
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Book Description
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.
Author: Charu C. Aggarwal
Publisher: Springer Science & Business Media
ISBN: 0387096906
Category : Computers
Languages : en
Pages : 494
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Book Description
Managing and Mining Uncertain Data, a survey with chapters by a variety of well known researchers in the data mining field, presents the most recent models, algorithms, and applications in the uncertain data mining field in a structured and concise way. This book is organized to make it more accessible to applications-driven practitioners for solving real problems. Also, given the lack of structurally organized information on this topic, Managing and Mining Uncertain Data provides insights which are not easily accessible elsewhere. Managing and Mining Uncertain Data is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a reference book for advanced-level students in computer science and engineering, as well as the ACM, IEEE, SIAM, INFORMS and AAAI Society groups.
Author: Morad Benyoucef
Publisher: Springer
ISBN: 3319179578
Category : Computers
Languages : en
Pages : 286
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Book Description
This book constitutes the refereed proceedings of the 6th International Conference on E-Technologies, MCETECH 2015, held in Montréal, Canada, in May 2015. The 18 papers presented in this volume were carefully reviewed and selected from 42 submissions. They have been organized in topical sections on process adaptation; legal issues; social computing; eHealth; and eBusiness, eEducation and eLogistics.
Author: AnHai Doan
Publisher: Elsevier
ISBN: 0124160441
Category : Computers
Languages : en
Pages : 522
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Book Description
How do you approach answering queries when your data is stored in multiple databases that were designed independently by different people? This is first comprehensive book on data integration and is written by three of the most respected experts in the field. This book provides an extensive introduction to the theory and concepts underlying today's data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. Data integration is the problem of answering queries that span multiple data sources (e.g., databases, web pages). Data integration problems surface in multiple contexts, including enterprise information integration, query processing on the Web, coordination between government agencies and collaboration between scientists. In some cases, data integration is the key bottleneck to making progress in a field. The authors provide a working knowledge of data integration concepts and techniques, giving you the tools you need to develop a complete and concise package of algorithms and applications.
Author: Salem Benferhat
Publisher: Springer
ISBN: 3642239633
Category : Computers
Languages : en
Pages : 574
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Book Description
This book constitutes the refereed proceedings of the 5th International Conference on Scalable Uncertainty Management, SUM 2011, held in Dayton, OH, USA, in October 2011. The 32 revised full papers and 3 revised short papers presented together with the abstracts of 2 invited talks and 6 “discussant” contributions were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on argumentation systems, probabilistic inference, dynamic of beliefs, information retrieval and databases, ontologies, possibility theory and classification, logic programming, and applications.
Author: Paolo Atzeni
Publisher: Springer
ISBN: 3642340024
Category : Computers
Languages : en
Pages : 608
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Book Description
This book constitutes the refereed proceedings of the 31st International Conference on Conceptual Modeling, ER 2012, held in Florence, Italy, in October 2012. The 24 regular papers presented together with 13 short papers, 6 poster papers and 3 keynotes were carefully reviewed and selected from 141 submissions. The papers are organized in topical sections on understandability and cognitive approaches; conceptual modeling for datawarehousing and business intelligence; extraction, discovery and clustering; search and documents; data and process modeling; ontology based approaches; variability and evolution; adaptation, preferences and query refinement; queries, matching and topic search; and conceptual modeling in action.
