Boolean query mapping across heterogeneous information sources

Kevin Chen Chuan Chang; Hector Garcia-Molina; Andreas Paepcke

doi:10.1109/69.536244

Boolean query mapping across heterogeneous information sources

Kevin Chen Chuan Chang, Hector Garcia-Molina, Andreas Paepcke

Research output: Contribution to journal › Article › peer-review

Abstract

Searching over heterogeneous information sources is difficult because of the nonuniform query languages. Our approach is to allow a user to compose Boolean queries in one rich front-end language. For each user query and target source, we transform the user query into a subsuming query that can be supported by the source but that may return extra documents. The results are then processed by a filter query to yield the correct final result. In this paper we introduce the architecture and associated algorithms for generating the supported subsuming queries and filters. We show that generated subsuming queries return a minimal number of documents; we also discuss how minimal cost filters can be obtained. We have implemented prototype versions of these algorithms and demonstrated them on heterogeneous Boolean systems.

Original language	English (US)
Pages (from-to)	515-521
Number of pages	7
Journal	IEEE Transactions on Knowledge and Data Engineering
Volume	8
Issue number	4
DOIs	https://doi.org/10.1109/69.536244
State	Published - 1996
Externally published	Yes

Keywords

Boolean queries
Digital libraries
Filtering
Heterogeneity
Information retrieval
Query subsumption
Query translation

ASJC Scopus subject areas

Information Systems
Computer Science Applications
Computational Theory and Mathematics

Online availability

10.1109/69.536244

Library availability

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title = "Boolean query mapping across heterogeneous information sources",

abstract = "Searching over heterogeneous information sources is difficult because of the nonuniform query languages. Our approach is to allow a user to compose Boolean queries in one rich front-end language. For each user query and target source, we transform the user query into a subsuming query that can be supported by the source but that may return extra documents. The results are then processed by a filter query to yield the correct final result. In this paper we introduce the architecture and associated algorithms for generating the supported subsuming queries and filters. We show that generated subsuming queries return a minimal number of documents; we also discuss how minimal cost filters can be obtained. We have implemented prototype versions of these algorithms and demonstrated them on heterogeneous Boolean systems.",

keywords = "Boolean queries, Digital libraries, Filtering, Heterogeneity, Information retrieval, Query subsumption, Query translation",

author = "Chang, {Kevin Chen Chuan} and Hector Garcia-Molina and Andreas Paepcke",

note = "Funding Information: This material is based upon work supported by the National Science Foundation under Cooperative Agreement IRI-9411306. Funding for this cooperative agreement is also provided by DARPA, NASA, and the industrial partners of the Stanford Digital Libraries Project.",

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AU - Garcia-Molina, Hector

AU - Paepcke, Andreas

N1 - Funding Information: This material is based upon work supported by the National Science Foundation under Cooperative Agreement IRI-9411306. Funding for this cooperative agreement is also provided by DARPA, NASA, and the industrial partners of the Stanford Digital Libraries Project.

PY - 1996

Y1 - 1996

N2 - Searching over heterogeneous information sources is difficult because of the nonuniform query languages. Our approach is to allow a user to compose Boolean queries in one rich front-end language. For each user query and target source, we transform the user query into a subsuming query that can be supported by the source but that may return extra documents. The results are then processed by a filter query to yield the correct final result. In this paper we introduce the architecture and associated algorithms for generating the supported subsuming queries and filters. We show that generated subsuming queries return a minimal number of documents; we also discuss how minimal cost filters can be obtained. We have implemented prototype versions of these algorithms and demonstrated them on heterogeneous Boolean systems.

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Boolean query mapping across heterogeneous information sources

Abstract

Keywords

ASJC Scopus subject areas

Online availability

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