Data model and query evaluation in global information systems

Levy, Alon Y.; Srivastava, Divesh; Kirk, Thomas

doi:10.1007/bf00962627

Cited by 165 publications

(74 citation statements)

References 14 publications

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“…Although there are a number of recent systems that follow this general scheme, for example [4,13,22], none of these systems scale up to an environment in which the number of potential sources is very large, and which is constantly changing (such as the World Wide Web). The primary limitation is that the process of incorporating new member schemes into the global scheme is complex and costly.…”

Section: Introductionmentioning

confidence: 99%

Autoplex: Automated Discovery of Content for Virtual Databases

Berlin

Motro

2001

Cooperative Information Systems

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Abstract. Most virtual database systems are suitable for environments in which the set of member information sources is small and stable. Consequently, present virtual database systems do not scale up very well. The main reason is the complexity and cost of incorporating new information sources into the virtual database. In this paper we describe a system, called Autoplex, which uses machine learning techniques for automating the discovery of new content for virtual database systems. Autoplex assumes that several information sources have already been incorporated ("mapped") into the virtual database system by human experts (as done in standard virtual database systems). Autoplex learns the features of these examples. It then applies this knowledge to new candidate sources, trying to infer views that "resemble" the examples. In this paper we report initial results from the Autoplex project.

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Section: Introductionmentioning

confidence: 99%

Autoplex: Automated Discovery of Content for Virtual Databases

Berlin

Motro

2001

Cooperative Information Systems

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“…In recent years, a number of distributed query-processing systems have been developed in which the global schema and user queries are expressed in some form of description logic (DL) (for example, TAMBIS [1], DWQ [2], Information Manifold [3], PICSEL [4], SIMS [5]). The use of a DL as both high-level data description language and query language has several advantages:…”

Section: Introductionmentioning

confidence: 99%

Estimating the quality of answers when querying over description logic ontologies

Peim

Franconi

Paton

2003

Data & Knowledge Engineering

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Information integration systems allow users to express queries over high-level conceptual models. However, such queries must subsequently be evaluated over collections of sources, some of which are likely to be expensive to use or subject to periods of unavailability. As such, it would be useful if information integration systems were able to provide users with estimates of the consequences of omitting certain sources from query execution plans. Such omissions can affect both the soundness (the fraction of returned answers which are returned) and the completeness (the fraction of correct answers which are returned) of the answer set returned by a plan. Many recent information integration systems have used conceptual models expressed in description logics (DLs). This paper presents an approach to estimating the soundness and completeness of queries expressed in the ALCQI DL. Our estimation techniques are based on estimating the cardinalities of query answers. We have have conducted some statistical evaluation of our techniques, the results of which are presented here. We also offer some suggestions as to how estimates for cardinalities of subqueries can be used to aid users in improving the soundness and completeness of query plans.

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“…In order to find good views, one has to understand how queries can be rewritten using views. Rewriting queries using views has been studied extensively for non-aggregate queries [LMSS95], and algorithms have been devised and implemented [LSK95,Qia96]. For aggregate queries, the problem has been investigated mainly in the special case of datacubes (see e.g., [HRU96,Dyr96].…”

Section: Introductionmentioning

confidence: 99%

Algorithms for Rewriting Aggregate Queries Using Views

Cohen

Nutt

Serebrenik³

2000

Current Issues in Databases and Information Systems

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Typical queries over data warehouses perform aggregation. One of the main ideas to optimize the execution of an aggregate query is to reuse results of previously answered queries. This leads to the problem of rewriting aggregate queries using views. More precisely, given a set of queries, called "views," and a new query, the task is to reformulate the new query with the help of the views in such a way that executing the reformulated query over the views yields the same result as executing the original query over the base relations. Due to a lack of theory, so far algorithms for this problem were rather ad-hoc. They were sound, but were not proven to be complete.In earlier work we have given syntactic characterizations for the equivalence of aggregate queries, and applied them decide when there exist rewritings. However, these decision procedures are highly nondeterministic and do not lend themselves immediately to an implementation.In the current paper, we refine those procedures by eliminating the nondeterminism as much as possible, thus obtaining practical algorithms for rewriting queries with the operators count and sum. It can be proved that our algorithms are complete for queries where each relation occurs only once and for queries without comparisons. We also show how algorithms for rewriting nonaggregateThe copyright of this paper belongs to the paper's authors. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage. Heidelberg, Germany, 14. -15.6. 1999 (S. Gatziu, M. Jeusfeld, M. Staudt, Y. Vassiliou, eds.) http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-19/ queries can be modified to obtain rewriting algorithms for queries with min and max. Proceedings of the International Workshop on Design and Management of Data Warehouses (DMDW'99)These algorithms are a basis for realizing optimizers that rewrite aggregate queries using views.

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Data model and query evaluation in global information systems

Cited by 165 publications

References 14 publications

Autoplex: Automated Discovery of Content for Virtual Databases

Autoplex: Automated Discovery of Content for Virtual Databases

Estimating the quality of answers when querying over description logic ontologies

Algorithms for Rewriting Aggregate Queries Using Views

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