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001 978-1-84628-284-3
003 DE-He213
005 20170628033850.0
007 cr nn 008mamaa
008 100301s2005 xxk| s |||| 0|eng d
020 _a9781846282843
_9978-1-84628-284-3
024 7 _a10.1007/1-84628-284-5
_2doi
050 4 _aQ334-342
050 4 _aTJ210.2-211.495
072 7 _aUYQ
_2bicssc
072 7 _aTJFM1
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aBandyopadhyay, Sanghamitra.
_eauthor.
245 1 0 _aAdvanced Methods for Knowledge Discovery from Complex Data
_h[electronic resource] /
_cby Sanghamitra Bandyopadhyay, Ujjwal Maulik, Lawrence B. Holder, Diane J. Cook.
264 1 _aLondon :
_bSpringer London,
_c2005.
300 _aXVIII, 369 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvanced Information and Knowledge Processing
505 0 _aFoundations -- Knowledge Discovery and Data Mining -- Automatic Discovery of Class Hierarchies via Output Space Decomposition -- Graph-based Mining of Complex Data -- Predictive Graph Mining with Kernel Methods -- TreeMiner: An Efficient Algorithm for Mining Embedded Ordered Frequent Trees -- Sequence Data Mining -- Link-based Classification -- Applications -- Knowledge Discovery from Evolutionary Trees -- Ontology-Assisted Mining of RDF Documents -- Image Retrieval using Visual Features and Relevance Feedback -- Significant Feature Selection Using Computational Intelligent Techniques for Intrusion Detection -- On-board Mining of Data Streams in Sensor Networks -- Discovering an Evolutionary Classifier over a High-speed Nonstatic Stream.
520 _aAdvanced Methods for Knowledge Discovery from Complex Data brings together research articles by active practitioners and leading researchers reporting recent advances in the field of knowledge discovery, where the information is mined from complex data, such as unstructured text from the world-wide web, databases naturally represented as graphs and trees, geoscientific data from satellites and visual images, multimedia data and bioinformatics data. An overview of the field, looking at the issues and challenges involved is followed by coverage of recent trends in data mining, including descriptions of some currently popular tools like genetic algorithms, neural networks and case-based reasoning. This provides the context for the subsequent chapters on methods and applications. Part I is devoted to the foundations of mining different types of complex data like trees, graphs, links and sequences. A knowledge discovery approach based on problem decomposition is also described. Part II presents important applications of advanced mining techniques to data in unconventional and complex domains, such as life sciences, world-wide web, image databases, cyber security and sensor networks. With a good balance of introductory material on the knowledge discovery process, advanced issues and state-of-the-art tools and techniques, as well as recent working applications this book provides a representative selection of the available methods and their evaluation in real domains. It will be useful to students at Masters and PhD level in Computer Science, as well as practitioners in the field. A website supports the book: http://www.cse.uta.edu/amkdcd.
650 0 _aComputer science.
650 0 _aComputer software.
650 0 _aDatabase management.
650 0 _aInformation storage and retrieval systems.
650 0 _aArtificial intelligence.
650 0 _aComputer vision.
650 0 _aOptical pattern recognition.
650 1 4 _aComputer Science.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aDatabase Management.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aPattern Recognition.
650 2 4 _aAlgorithm Analysis and Problem Complexity.
650 2 4 _aImage Processing and Computer Vision.
700 1 _aMaulik, Ujjwal.
_eauthor.
700 1 _aHolder, Lawrence B.
_eauthor.
700 1 _aCook, Diane J.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781852339890
830 0 _aAdvanced Information and Knowledge Processing
856 4 0 _uhttp://dx.doi.org/10.1007/1-84628-284-5
912 _aZDB-2-SCS
999 _c17202
_d17202