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Learning structure and schemas from heterogeneous domains in networked systems surveyed

Author
Biba, M.; Xhafa, F.
Type of activity
Journal article
Journal
Studies in computational intelligence
Date of publication
2011
Volume
375
First page
1
Last page
16
DOI
https://doi.org/10.1007/978-3-642-22913-8_1 Open in new window
URL
https://link.springer.com/chapter/10.1007/978-3-642-22913-8_1 Open in new window
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 fo...
Keywords
Data mining, Learn structure, Malicious node, Multiple kernel learning, Sensor network
Group of research
ALBCOM - Algorithms, Computational Biology, Complexity and Formal Methods

Participants