Abbreviation Expansion in Schema Matching and Web Integration

Ratinov, Lev; Gudes, Ehud

doi:10.1109/wi.2004.10083

Cited by 10 publications

(9 citation statements)

References 6 publications

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“…For instance, the OTA standard 3 contains a list of recommended schema standard abbreviations. On the other hand, ad hoc abbreviations are mainly created by a schema designer to save space, and created from phrases that would not be abbreviated in textual sources (where there are no term length limitation) [11,12].…”

Section: Abbreviation Expansionmentioning

confidence: 99%

“…We use the Stanford part of speech tagger [18]. 11 If the CN does not fall under the endocentric syntactic structure (noun-noun or adjective-noun where the adjective derives from a noun), then it is ignored. For example, the constituents of the CN "Delivery Company" both belong to the noun syntactic category; 2.…”

Section: Step 1: Cn Constituent Disambiguationmentioning

confidence: 99%

“…10 These tests have been performed on several real data sources, containing several CNs, in different domains and formats (relational and XML): the first three levels of a subtree of the Yahoo and Google directories ("society and culture" and "society", respectively); three schemata of an application scenario (ICT-A partner search) of the NeP4B project, available at www.dbgroup.unimo.it/nep4b/NeP4BScenarioICTA.xml; the test schemata number 6 (RDB vs. Star datawarehouse schema) and the test schemata number 5 available at (CIDX and Excel) used in [17], and available at http://dit.unitn.it/~accord/ Experimentaldesign.html. 11 The Stanford part of speech tagger is freely available at http://nlp.stanford.edu/software/tagger.shtml.…”

Section: Step 1: Cn Constituent Disambiguationmentioning

confidence: 99%

“…The problem of ad hoc abbreviations has been further addressed by Ratinov and Gudes [11] by employing an external text corpus as the source for potential abbreviation expansions. The authors focus on the extraction of possible expansions for a given abbreviation but they do not provide any support to select the most relevant one.…”

Section: Normalization Techniques In Schema Matching Systemsmentioning

confidence: 99%

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Schema label normalization for improving schema matching

Sorrentino

Bergamaschi

Gawinecki

et al. 2010

Data & Knowledge Engineering

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Section: Abbreviation Expansionmentioning

confidence: 99%

Section: Step 1: Cn Constituent Disambiguationmentioning

confidence: 99%

Section: Step 1: Cn Constituent Disambiguationmentioning

confidence: 99%

Section: Normalization Techniques In Schema Matching Systemsmentioning

confidence: 99%

See 2 more Smart Citations

Schema label normalization for improving schema matching

Sorrentino

Bergamaschi

Gawinecki

et al. 2010

Data & Knowledge Engineering

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“…"Ind" (Indicator). On the contrary, ad hoc abbreviations are mainly created to save space, from phrases that would not be abbreviated in a normal context [22,11].…”

Section: Automatic Abbreviations Expansionmentioning

confidence: 99%

Schema Normalization for Improving Schema Matching

Sorrentino

Bergamaschi

Gawinecki

et al. 2009

Conceptual Modeling - ER 2009

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Abstract. Schema matching is the problem of finding relationships among concepts across heterogeneous data sources (heterogeneous in format and in structure). Starting from the "hidden meaning" associated to schema labels (i.e. class/attribute names) it is possible to discover relationships among the elements of different schemata. Lexical annotation (i.e. annotation w.r.t. a thesaurus/lexical resource) helps in associating a "meaning" to schema labels. However, accuracy of semi-automatic lexical annotation methods on real-world schemata suffers from the abundance of non-dictionary words such as compound nouns and word abbreviations. In this work, we address this problem by proposing a method to perform schema labels normalization which increases the number of comparable labels. Unlike other solutions, the method semi-automatically expands abbreviations and annotates compound terms, with a minimal manual effort. We empirically prove that our normalization method helps in the identification of similarities among schema elements of different data sources, thus improving schema matching accuracy.

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Non-binary evaluation measures for big data integration

Sagi

Gal

2017

The VLDB Journal

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Abbreviation Expansion in Schema Matching and Web Integration

Cited by 10 publications

References 6 publications

Schema label normalization for improving schema matching

Schema label normalization for improving schema matching

Schema Normalization for Improving Schema Matching

Non-binary evaluation measures for big data integration

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