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delete2007-02-01
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PRE
AI
J
José Luis Arjona *
R
Rafael Corchuelo
D
David Ruiz
M
Miguel Toro
DOI:10.1109/TKDE.2007.31delete
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Abstract

Abstract

En 中文
One the most challenging problems for Enterprise Information Integration is to deal with heterogeneous information sources on the Web. The reason is that they usually provide information that is in human-readable form only, which makes it difficult for a software agent,to understand it. Current solutions build on the idea of annotating the information with semantics. If the information is unstructured, proposals such as S-CREAM, MnM, or Armadillo may be effective enough since they rely on using natural language processing techniques; furthermore, their accuracy can be improved by using redundant information on the Web, as C-PANKOW has proved recently. If the information is structured and closely related to a back-end database, Deep Annotation ranges among the most effective proposals, but it requires the information providers to modify their applications; if Deep Annotation is not applicable, the easiest solution consists of using a wrapper and transforming its output into annotations. In this paper, we prove that this transformation can be automated by means of an efficient, domain-independent algorithm. To the best of our knowledge, this is the first attempt to devise and formalize such a systematic, general solution.
Keywords:
Enterprise Information Integration
wrappers
semiautomatic annotation
AI Summary

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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Knowledge and Data Engineering cover
IEEE Transactions on Knowledge and Data Engineering
IF:
10.4
Papers:
6.7K
Citations:
3.2W

Organization

Universidad de Huelva cover
Universidad de Huelva
Scholars:
2.8K
Papers: 2.6K
Citations: 2.2K
U
University of Sevilla
Scholars:
1.9W
Papers: 1.7W
Citations: 15