Selection of Semantical Mapping of Attribute Values for Data Integration

Szymczak, Marcin; Bronselaer, Antoon; Zadrożny, Sławomir; Tré, Guy De

doi:10.1007/978-3-319-11313-5_51

Cited by 1 publication

(3 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The high precision is important because these mappings are used by the implicit mappers: any false positive mappings are propagated by implicit mappers what lowers the overall result. Besides that, it is not crucial to detect all posible coreferent mappings but it is sufficient if the algorithm creates at least one coreferent mapping for each category which turns out to be the proper mapping (the selection of mappings is out of the scope of this paper and is investigated in [23]). The results in the last column confirm that, for around half of the categories from the source at least one coreferent mapping is established which is different from root with the precision equals 0.93.…”

Section: Evaluation and Discussionmentioning

confidence: 99%

“…However, it may be crucial to select for each value from the source exactly one from the target. Thus, more sophisticated selection method than the method which is based on the lowest uncertainty about mapping have to be investigated [23]. Moreover, our method can be easily applied for data integration or interoperability tasks.…”

Section: Discussionmentioning

confidence: 99%

“…Such a relationship can be further processed to reduce it to a one-to-one form. Such a processing as well as classification of a mapping as equivalent or non-equivalent may be needed in data integration, but this is out of the scope of this paper and it is studied, e.g., in [23].…”

Section: B Algorithmmentioning

confidence: 99%

See 2 more Smart Citations

Semantical mapping of attribute values for data integration

Szymczak

Bronselaer

Zadrożny

et al. 2014

2014 IEEE Conference on Norbert Wiener in the 21st Century (21CW)

Self Cite

View full text Add to dashboard Cite

Abstract-Nowadays the amount of data is increasing very fast. Moreover, useful information is scattered over multiple sources. Therefore, automatic data integration that guarantees high data quality is extremely important. One of the crucial operations in integration of information from independent databases is detection of different representations of the same piece of information (called coreferent data) and translation of the representation of data from one source into the representation of the other source. That translation is also known as object mapping. In this paper, we investigate automatic mapping methods for attributes the values of which may need semantical comparison and can be sorted by means of an order relation that reflects a notion of generality. These mapping methods are investigated closely in terms of their effectiveness. An experimental evaluation of our method shows that using different mapping methods can enlarge a set of true positive mappings.

show abstract

Section: Evaluation and Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%