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Learning Structure and Schemas from Heterogeneous Domains in Networked Systems Surveyed

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Learning Structure and Schemas from Documents

Part of the book series: Studies in Computational Intelligence ((SCI,volume 375))

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Abstract

With the continuous growing amount of digital documents in many different formats and with the increasing possibility to access these through internet-based technologies in distributed environments, there is strong motivation to develop robust methods to organize documents in large and repositories. In particular, the extremely large volume of document collections makes it unfeasible to manually handle such documents. In addition, most of the documents exist in an unstructured form and do not follow any schemas. Therefore, research efforts in this direction are being dedicated to automatically infer structure and schemas. This is essential in order to properly organize huge collections as well as to effectively and efficiently retrieve documents in in . This chapter presents a survey of the state-of-the-art methods for inferring structure from documents and schemas in networked environments. The survey is organized around important application domains such as bio-informatics, sensor networks, social networks, P2P systems, automation and control, transportation and privacy-preserving for which we analyze the recent developments on dealing with unstructured data in such domains.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of New York, Tirana, Albania

    Marenglen Biba

  2. Technical University of Catalonia, Barcelona, Spain

    Fatos Xhafa

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  1. Marenglen Biba
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  2. Fatos Xhafa
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Editors and Affiliations

  1. University of New York Tirana, Rr. Komuna E Parisit,, Tirana, Albania

    Marenglen Biba

  2. Technical University of Catalonia, Campus Nord, Ed. Omega, C/Jordi Girona 1-3, 08034, Barcelona, Spain

    Fatos Xhafa

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Biba, M., Xhafa, F. (2011). Learning Structure and Schemas from Heterogeneous Domains in Networked Systems Surveyed. In: Biba, M., Xhafa, F. (eds) Learning Structure and Schemas from Documents. Studies in Computational Intelligence, vol 375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22913-8_1

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  • DOI: https://doi.org/10.1007/978-3-642-22913-8_1

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