2001•ACM Transactions on Database SystemsRequires access

Answering queries with useful bindings

Chen Li, Edward Yi Chang

Open publisher page 51 citations

Abstract

In information-integration systems, sources may have diverse and limited query capabilities. To obtain maximum information from these restrictive sources to answer a query, one can access sources that are not specified in the query (i.e., off-query sources). In this article, we propose a query-planning framework to answer queries in the presence of limited access patterns. In the framework, a query and source descriptions are translated to a recursive datalog program. We then solve optimization problems in this framework, including how to decide whether accessing off-query sources is necessary, how to choose useful sources for a query, and how to test query containment. We develop algorithms to solve these problems, and thus construct an efficient program to answer a query.

About this research paper

What this paper is about

In information-integration systems, sources may have diverse and limited query capabilities. To obtain maximum information from these restrictive sources to answer a query, one can access sources that are not specified in the query (i.e., off-query sources). In this article, we propose a query-planning framework to answer queries in the presence of limited access patterns. In the framework, a query and source descriptions are translated to a recursive datalog program. We then solve optimization problems in this framework, including how to decide whether accessing off-query sources is necessary, how to choose useful sources for a query, and how to test query containment. We develop algorithms to solve these problems, and thus construct an efficient program to answer a query.

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OpenAlex reports 51 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In information-integration systems, sources may have diverse and limited query capabilities. To obtain maximum information from these restrictive sources to answer a query, one can access sources that are not specified in the query (i.e., off-query sources). In this article, we propose a query-planning framework to answer queries in the presence of limited access patterns. In the framework, a query and source descriptions are translated to a recursive datalog program. We then solve optimization problems in this framework, including how to decide whether accessing off-query sources is necessary, how to choose useful sources for a query, and how to test query containment. We develop algorithms to solve these problems, and thus construct an efficient program to answer a query.

Key concepts: Computer science, Query optimization, Sargable, Query language, Query expansion, Web query classification, Web search query, Information retrieval

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