By Ujjwal Maulik, Lawrence B. Holder, Diane J. Cook
This e-book brings jointly learn articles by way of energetic practitioners and major researchers reporting fresh advances within the box of data discovery. an summary of the sector, taking a look at the problems and demanding situations concerned is through assurance of modern developments in facts mining. this gives the context for the following chapters on equipment and functions. half I is dedicated to the principles of mining sorts of complicated info like timber, graphs, hyperlinks and sequences. an information discovery strategy in keeping with challenge decomposition is additionally defined. half II offers vital purposes of complex mining options to info in unconventional and complicated domain names, akin to lifestyles sciences, world-wide internet, snapshot databases, cyber safety and sensor networks. With a very good stability of introductory fabric at the wisdom discovery approach, complex matters and cutting-edge instruments and methods, this ebook may be priceless to scholars at Masters and PhD point in computing device technology, in addition to practitioners within the box.
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Additional resources for Advanced Methods for Knowledge Discovery from Complex Data
1 Content-based Retrieval Sometimes users of a data mining system are interested in one or more patterns that they want to retrieve from the underlying data. These tasks, commonly known as content-based retrieval, are mostly used for text and image databases. For example, searching the web uses a page ranking technique that is based on link patterns for estimating the relative importance of diﬀerent pages with respect to the current search. In general, the diﬀerent issues in content-based retrieval are as follows: • Identifying an appropriate set of features used to index an object in the database; • Storing the objects, along with their features, in the database; • Deﬁning a measure of similarity between diﬀerent objects; • Given a query and the similarity measure, performing an eﬃcient search in the database; • Incorporating user feedback and interaction in the retrieval process.
Pattern Recognition Letters, 19, 1171–81.  — 1999: Theoretical performance of genetic pattern classiﬁer. J. Franklin Institute. 336, 387–422. , and S. K. Pal, 1997: Pattern classiﬁcation with genetic algorithms: Incorporation of chromosome diﬀerentiation. Pattern Recognition Letters, 18, 119–31. , S. K. Pal and U. Maulik, 1998: Incorporating chromosome diﬀerentiation in genetic algorithms. Information Science, 104, 293–319. , R. Shamir and Z. Yakhini, 1999: Clustering gene expression patterns.
Proceedings of KDD 96 , Portland, Oregon, 20–26.  Inmon, W. , 1996: The data warehouse and data mining. Communications of the ACM , 39, 49–50.  Jain, A. K. and R. C. Dubes, 1988: Algorithms for Clustering Data. Prentice-Hall, Englewood Cliﬀs, NJ.  Jensen, F. , 1996: An Introduction to Bayesian Networks. SpringerVerlag, New York, USA. , S. Bandyopadhyay and B. H. , 2005: Special Issue on Distributed and Mobile Data Mining, IEEE Transactions on Systems, Man, and Cybernetics Part B. IEEE.