Searching Databases with Keywords

Wang, Shan; Zhang, Kunlong

doi:10.1007/s11390-005-0006-4

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Cited by 29 publications

(2 citation statements)

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“…The dielectric constant (k), density (q), and the porosity (p) were calculated from the following expressions [12,13], which were empirical and used for silica aerogels k ¼ 1 þ 6:33ðn À 1Þ; ð1Þ q ¼ ðn À 1Þ=0:202;…”

Section: Resultsmentioning

confidence: 99%

Fluorinated nanoporous SiO2 films with ultra-low dielectric constant

Zhen

Zhang

et al. 2008

Journal of Non-Crystalline Solids

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Section: Resultsmentioning

confidence: 99%

Fluorinated nanoporous SiO2 films with ultra-low dielectric constant

Zhen

Zhang

et al. 2008

Journal of Non-Crystalline Solids

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“…The earlier survey in [8] and [9] overviewed systems such as BANKS [10], DBXplorer [3], DISCOVER [4], ObjectRank [2], and EASE [11] and briefly summarized the key techniques from several aspects.…”

Section: Related Workmentioning

confidence: 99%

A Metadata Search Approach to Keyword Query in Relational Databases

Saelee¹,

Boonjing²

2013

IJCA

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This paper proposes an effective approach to keyword query in relational databases. It uses a semantic graph model consisting of database metadata, database values, user terms, and their semantic connections. Keywords of a query determine all possible connected subgraphs of the semantic model. A query answer is a subgraph with the minimum connections. In addition, the approach proposes to rank result tuples of the answer subgraph using the IR-style ranking function. Our experiment results show that queries with metadata terms give more precise answers than queries without them. General Terms

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