1 edition of Uncertain schema matching found in the catalog.
Uncertain schema matching
by Morgan & Claypool in San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA)
Written in English
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.
|Other titles||Synthesis digital library of engineering and computer science.|
|Series||Synthesis lectures on data management -- # 13|
|LC Classifications||QA76.9.D338 G258 2011|
|The Physical Object|
|Format||[electronic resource] /|
|ISBN 10||9781608454341, 9781608454334|
He authored the book Uncertain schema Matching in and he co-authored the paper "Complex Event Processing over Uncertain Data", which received the test-of-time award in DEBS Prof. Gal serves in various editorial capacities for periodicals and has helped organize professional workshops and conferences. He has won IBM, Accenture, and JP. Data integration techniques provide a communication bridge between isolated sources and offer a platform for information exchange. When the schemas of heterogeneous data sources map to the centralized schema in a mediated data integration system or a source schema maps to a target schema in a peer-to-peer system, multiple schema mappings may exist due to the ambiguities Author: Longzhuang Li, Feng Tian, Yonghuai Liu, Shanxian Mao.
Children’s play can involve a single schema or several schemas all at once. For example, children playing with toy cars may be exploring a combination of transporting, rotation and trajectory. Trajectory Schema Throwing toys, dropping objects, splashing in the water, climbing and jumping off furniture are all activities in the trajectory Size: 1MB. Mediated Schema. The mediated schema A data integration system that manages uncertainty would be able to model uncertain data, uncertain schema mappings, and uncertain queries. about probabilistic modeling in databases and about how probabilities can be computed for the outputs of semiautomated schema matching techniques. View chapter.
Schema Matching, Industrial-Scale, Experience, Decision Makers. 1. Introduction The database community has been conducting research on schema matching for decades . This research has usually assumed that schema matching (i.e., the generation of semantic correspondences among schemata) is merely a precursor to the. Schema Matching. Match schema attributes by value similarity. Usage. Run./schema-matching --help to see a usage description.. Examples. See the shell scripts in demo.I suggest that you start with for something simple. The output will be, in this order.
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Uncertain Schema Matching. Abstract. 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. Uncertain schema matching , concedes that schema matching is an inherently uncertain process and maintains the uncertainty recorded by the schema matching process.
This 1 2 www Author: Avigdor Gal. Find many great new & used options and get the best deals for Synthesis Lectures on Data Management: Uncertain Schema Matching by Avigdor Gal (, Paperback) at the best online prices at eBay.
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Get this from a library. Uncertain schema matching. [Avigdor Gal] -- 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. Although schema matching research has been ongoing for over 25 years, more recently a realization has emerged that schema matchers are inherently uncertain. Sincework on the uncertainty in schema matching has picked up, along with research Uncertain schema matching book uncertainty in other areas of data management.
These challenges require the development of a set of methods to support a matching process using uncertainty management tools to quantify the inherent uncertainty in the process.
This chapter is devoted to the introduction of uncertain schema matching. It also discusses existing and future research, as well as possible applications. UNCERTAIN SCHEMA MATCHING AVIGDOR GAL book, also in various other countries or cities.
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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 Uncertain.
Gal - Uncertain Schema Matching. Morgan & Claypool Publishers, 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. Although schema matching research has been ongoing for over 25 years, more recently a realization has emerged that schema matchers are inherently uncertain.
Sincework on the uncertainty in schema matching has picked up, along with research on uncertainty in other areas of data management.5/5(1). Schema matching supports data integration by establishing Since the matching process is inherently uncertain, schemas and not only in a pairwise setting.
Here of knowing whether a correspondence is correct is measured “Webtables: exploring the power of tables on the we,” in PVLDB.pp. Webtables: exploring the power of tables on the web. The terms schema matching and mapping are often used interchangeably for a database process.
For this article, we differentiate the two as follows: Schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects. For example, in the two schemas t (Name.
He authored the book Uncertain schema Matching inserves in various editorial capacities for periodicals including theJournal on Data Semantics (JoDS), Encyclopedia of Database Systems and Computing, and has helped organize professional workshops and conferences nearly every year since Schema matching is a central challenge for data integration sys-tems.
Automated tools are often uncertain about schema matchings they suggest, and this uncertainty is inherent since it arises from the inability of the schema to fully capture the semantics of the repre-sented data. Human common sense can often help.
Inspired by. Hybrid Schema Matching for Deep Web DOI: /_ In book: Intelligent Computing and Information n mappings. The quality of our uncertain schema matching algorithm is.
Despite advances in machine learning technologies a schema matching result between two database schemas (e.g., those derived from COMA++) is likely to be imprecise. In particular, numerous instances of “possible mappings” between the schemas may be derived from the matching result.
In this paper, we study problems related to managing possible mappings Cited by: Schema Matching and Mapping February February Read More.
Authors: Zohra Bellahsene, Angela Bonifati, Erhard Rahm; Publisher: Springer Publishing Company, Incorporated; ISBN: Pages: Available at Amazon. Save to Binder Binder Export Citation Citation. Share on. (TOIT), and the VLDB Journal), books (Schema Matching and Mapping), and conferences (ICDE, CIKM, ER, CoopIS, BPM).
He is the author of the book \Uncertain Schema Matching", part of Synthesis Lectures on Data Management (March ) and a co-author of a recent paper in the Infor-mation Systems Journal, \MFIBlocks: An e ective blocking. Modeling, Querying, and Mining Uncertain XML Data: /ch This chapter deals with data mining in uncertain XML data models, whose uncertainty typically comes from imprecise automatic processes.
We first review theCited by: 2. Managing Uncertainty in Schema Matching with Top-K Schema Mappings 91 elements of one schema to elements of the other. The outputted mapping is considered to be the best of all possible mappings between these schemata.
Although these tools comprise a signiﬁcant step towards fulﬁlling the vision.Managing Uncertainty in Schema Matching with Top-K Schema Mappings Avigdor Gal Abstract In this paper, we propose to extend current practice in schema matching with the simultaneous use of top-K schema mappings rather than a single best mapping.
This is a natural extension of existing methods (which can be considered to fall into the.Pay-as-you-go Reconciliation in Schema Matching Networks. Proceedings of the 30th International Conference on Data Engineering (ICDE ). Chicago, Illinois, USA, March T.
Sagi, A. Gal - Schema Matching Prediction with Applications to Data Source Discovery and Dynamic Ensembling. VLDB Journal, 22(5), September