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Extraction and Exploitation of Intensional Knowledge from Heterogeneous Information Sources

Semi-Automatic Approaches and Tools

  • Domenico Ursino

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2282)

Table of contents

  1. Front Matter
    Pages I-XXVI
  2. Introduction

    1. Pages 1-22
  3. Property Extraction

  4. Construction of a Cooperative Information System and of a Data Warehouse

  5. System Description and Experimentations

  6. Final Issues

    1. Front Matter
      Pages 252-253
    2. Pages 255-265
    3. Pages 267-267
  7. Back Matter
    Pages 269-289

About this book

Introduction

The problem of integrating multiple information sources into a uni?ed data store is currently one of the most important challenges in data management. Within the ?eld of source integration, the problem of automatically gen- ating an integrated description of the data sources is surely one of the most relevant. The signi?cance of the issue can be best understood if one c- siders the huge number of information sources that an organization has to integrate. Indeed, it is even impossible to try to do all the work by hand. Like other important issues in data management, the problem of integrating multiple data sources into a unique global system has several facets, each of which represents, “per se”, an interesting research problem, and comprises, for instance, that of recognizing, at the intensional level, similarities and dissimilarities among scheme objects, that of resolving representation m- matches among schemes, and that of deciding how to obtain an integrated data store out of a set of input sources and of a semantic description of their contents. The research and application relevance of such issues has attracted wide interest in the database community in recent years. And, as a con- quence, several techniques have been presented in the literature attacking one side or another of this complex and multifarious problem.

Keywords

Data Integration Database Integration Distributed Databases algorithms computer science control data mining data warehouse database information extraction information system knowledge knowledge representation learning system

Authors and affiliations

  • Domenico Ursino
    • 1
  1. 1.DIMET -Dipartimento di Informatica, Matematica, Elettronica e TrasportiUniversità degli Studi di Reggio CalabriaReggio CalabriaItaly

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-70735-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2002
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-43347-7
  • Online ISBN 978-3-540-70735-6
  • Series Print ISSN 0302-9743
  • Buy this book on publisher's site