COMA - A system for flexible combination of schema matching approaches”. (2002)

by Hong-Hai Do, Erhad Rahm
Venue:Proceedings of the 28th VLDB Conference.
Add To MetaCart
Results 1 - 10 of 440

A classification of schema-based matching approaches

by Pavel Shvaiko - JOURNAL ON DATA SEMANTICS , 2005
"... Schema/ontology matching is a critical problem in many application domains, such as, semantic web, schema/ontology integration, data warehouses, e-commerce, catalog matching, etc. Many diverse solutions to the matching problem have been proposed so far. In this paper we present a taxonomy of schema- ..."
Abstract - Cited by 386 (21 self) - Add to MetaCart
Schema/ontology matching is a critical problem in many application domains, such as, semantic web, schema/ontology integration, data warehouses, e-commerce, catalog matching, etc. Many diverse solutions to the matching problem have been proposed so far. In this paper we present a taxonomy of schema-based matching techniques that builds on the previous work on classifying schema matching approaches. Some innovations are in introducing new criteria which distinguish between matching techniques relying on diverse semantic clues. In particular, we distinguish between heuristic and formal techniques at schemalevel; and implicit and explicit techniques at element- and structure-level. Based on the classification proposed we overview some of the recent schema/ontology matching systems pointing which part of the solution space they cover.

Translating Web Data

by Lucian Popa, Yannis Velegrakis, Renee J. Miller, Mauricio A. Hernandez, Ronald Fagin - In VLDB , 2002
"... We present a novel framework for mapping between any combination of XML and relational schemas, in which a high-level, userspecified mapping is translated into semantically meaningful queries that transform source data into the target representation. Our approach works in two phases. In the first ph ..."
Abstract - Cited by 229 (40 self) - Add to MetaCart
We present a novel framework for mapping between any combination of XML and relational schemas, in which a high-level, userspecified mapping is translated into semantically meaningful queries that transform source data into the target representation. Our approach works in two phases. In the first phase, the high-level mapping, expressed as a set of inter-schema correspondences, is converted into a set of mappings that capture the design choices made in the source and target schemas (including their hierarchical organization as well as their nested referential constraints).

Comparison of Schema Matching Evaluations

by Hong-hai Do, Sergey Melnik, Erhard Rahm - In Proceedings of the 2nd Int. Workshop on Web Databases (German Informatics Society , 2002
"... Recently, schema matching has found considerable interest in both research and practice. Determining matching components of database or XML schemas is needed in many applications, e.g. for E-business and data integration. ..."
Abstract - Cited by 186 (7 self) - Add to MetaCart
Recently, schema matching has found considerable interest in both research and practice. Determining matching components of database or XML schemas is needed in many applications, e.g. for E-business and data integration.
(Show Context)

S-match: an algorithm and an implementation of semantic matching

by Fausto Giunchiglia, Pavel Shvaiko, Mikalai Yatskevich, Fausto Giunchiglia, Pavel Shvaiko, Mikalai Yatskevich - In Proceedings of ESWS , 2004
"... semantic matching ..."
Abstract - Cited by 182 (33 self) - Add to MetaCart
semantic matching
(Show Context)

QOM – Quick ontology mapping

by Marc Ehrig, Steffen Staab - In Proc. 3rd International Semantic Web Conference (ISWC04 , 2004
"... Abstract. (Semi-)automatic mapping — also called (semi-)automatic alignment — of ontologies is a core task to achieve interoperability when two agents or services use different ontologies. In the existing literature, the focus has so far been on improving the quality of mapping results. We here cons ..."
Abstract - Cited by 150 (10 self) - Add to MetaCart
Abstract. (Semi-)automatic mapping — also called (semi-)automatic alignment — of ontologies is a core task to achieve interoperability when two agents or services use different ontologies. In the existing literature, the focus has so far been on improving the quality of mapping results. We here consider QOM, Quick Ontology Mapping, as a way to trade off between effectiveness (i.e. quality) and efficiency of the mapping generation algorithms. We show that QOM has lower run-time complexity than existing prominent approaches. Then, we show in experiments that this theoretical investigation translates into practical benefits. While QOM gives up some of the possibilities for producing high-quality results in favor of efficiency, our experiments show that this loss of quality is marginal. 1
(Show Context)

Meteor-S Web Service annotation framework

by Abhijit Patil, Swapna Oundhakar, Amit Sheth, Kunal Verma - In Proceedings of the 13th International Conference on the World Wide Web , 2004
"... The World Wide Web is emerging not only as an infrastructure for data, but also for a broader variety of resources that are increasingly being made available as Web services. Relevant current standards like UDDI, WSDL, and SOAP are in their fledgling years and form the basis of making Web services a ..."
Abstract - Cited by 147 (16 self) - Add to MetaCart
The World Wide Web is emerging not only as an infrastructure for data, but also for a broader variety of resources that are increasingly being made available as Web services. Relevant current standards like UDDI, WSDL, and SOAP are in their fledgling years and form the basis of making Web services a workable and broadly adopted technology. However, realizing the fuller scope of the promise of Web services and associated service oriented architecture will requite further technological advances in the areas of service interoperation, service discovery, service composition, and process orchestration. Semantics, especially as supported by the use of ontologies, and related Semantic Web technologies, are likely to provide better qualitative and scalable solutions to these requirements. Just as semantic annotation of data in the Semantic Web is the first critical step to better search, integration and analytics over heterogeneous data, semantic annotation of Web services is an equally critical first step to achieving the above promise. Our approach is to work with existing Web services technologies and combine them with ideas from the Semantic Web to create a better framework for Web service discovery and composition. In this paper we present MWSAF (METEOR-S Web Service Annotation Framework), a framework for semi-automatically marking up Web service descriptions with ontologies. We have developed algorithms to match and annotate WSDL files with relevant ontologies. We use domain ontologies to categorize Web services into domains. An empirical study of our approach is presented to help evaluate its performance.
(Show Context)

Semantic integration research in the database community: A brief survey

by Anhai Doan, Alon Y. Halevy - AI Magazine , 2005
"... Semantic integration has been a long-standing challenge for the database community. It has received steady attention over the past two decades, and has now become a prominent area of database research. In this article, we first review database applications that require semantic integration, and disc ..."
Abstract - Cited by 145 (4 self) - Add to MetaCart
Semantic integration has been a long-standing challenge for the database community. It has received steady attention over the past two decades, and has now become a prominent area of database research. In this article, we first review database applications that require semantic integration, and discuss the difficulties underlying the integration process. We then describe recent progress and identify open research issues. We will focus in particular on schema matching, a topic that has received much attention in the database community, but will also discuss data matching (e.g., tuple deduplication), and open issues beyond the match discovery context (e.g., reasoning with matches, match verification and repair, and reconciling inconsistent data values). For previous surveys of database research on semantic integration, see (Rahm & Bernstein 2001;

iMAP: discovering complex semantic matches between database schemas

by Robin Dhamankar, Yoonkyong Lee, Anhai Doan, Alon Halevy, Pedro Domingos - in: Proceedings of the 2004 ACM SIGMOD International Conference on Management of Data, ACM , 2004
"... Creating semantic matches between disparate data sources is fundamental to numerous data sharing efforts. Manually creating matches is extremely tedious and error-prone. Hence many recent works have focused on automating the matching process. To date, however, virtually all of these works deal only ..."
Abstract - Cited by 140 (3 self) - Add to MetaCart
Creating semantic matches between disparate data sources is fundamental to numerous data sharing efforts. Manually creating matches is extremely tedious and error-prone. Hence many recent works have focused on automating the matching process. To date, however, virtually all of these works deal only with one-to-one (1-1) matches, such as address = location. They do not consider the important class of more complex matches, such as address = concat(city,state) and room-price = room-rate * (1 + tax-rate). We describe the iMAP system which semi-automatically discovers both 1-1 and complex matches. iMAP reformulates schema matching as a search in an often very large or infinite match space. To search effectively, it employs a set of searchers, each discovering specific types of complex matches. To further improve matching accuracy, iMAP exploits a variety of domain knowledge, including past complex matches, domain integrity constraints, and overlap data. Finally, iMAP introduces a novel feature that generates explanation of predicted matches, to provide insights into the matching process and suggest actions to converge on correct matches quickly. We apply iMAP to several real-world domains to match relational tables, and show that it discovers both 1-1 and complex matches with high accuracy. 1.
(Show Context)

Overview of record linkage and current research directions

by William E Winkler - BUREAU OF THE CENSUS , 2006
"... This paper provides background on record linkage methods that can be used in combining data from a variety of sources such as person lists business lists. It also gives some areas of current research. ..."
Abstract - Cited by 139 (1 self) - Add to MetaCart
This paper provides background on record linkage methods that can be used in combining data from a variety of sources such as person lists business lists. It also gives some areas of current research.

Ontology Mapping - An Integrated Approach

by Marc Ehrig, York Sure , 2004
"... Ontology mapping is important when working with more than one ontology. Typically similarity considerations are the basis for this. In this paper an approach to integrate various similarity methods is presented. In brief, we determine similarity through rules which have been encoded by ontology e ..."
Abstract - Cited by 137 (9 self) - Add to MetaCart
Ontology mapping is important when working with more than one ontology. Typically similarity considerations are the basis for this. In this paper an approach to integrate various similarity methods is presented. In brief, we determine similarity through rules which have been encoded by ontology experts.
(Show Context)