Download PDF by Ujjwal Maulik, Lawrence B. Holder, Diane J. Cook: Advanced Methods for Knowledge Discovery from Complex Data

By Ujjwal Maulik, Lawrence B. Holder, Diane J. Cook

ISBN-10: 1852339896

ISBN-13: 9781852339890

This e-book brings jointly study articles by means of energetic practitioners and major researchers reporting contemporary advances within the box of information discovery. an outline of the sphere, the problems and demanding situations concerned is via assurance of contemporary traits in information mining. this offers the context for the next chapters on equipment and functions. half I is dedicated to the rules of mining kinds of advanced info like timber, graphs, hyperlinks and sequences. a data discovery technique in line with challenge decomposition is usually defined. half II provides very important functions of complicated mining ideas to facts in unconventional and complicated domain names, equivalent to existence sciences, world-wide net, snapshot databases, cyber defense and sensor networks. With an excellent stability of introductory fabric at the wisdom discovery technique, complicated matters and cutting-edge instruments and methods, this e-book might be worthy to scholars at Masters and PhD point in desktop technology, in addition to practitioners within the box.

Show description

Read Online or Download Advanced Methods for Knowledge Discovery from Complex Data PDF

Similar data mining books

Download e-book for iPad: Principles of Data Mining (2nd Edition) (Undergraduate by Max Bramer

Info Mining, the automated extraction of implicit and possibly invaluable info from facts, is more and more utilized in advertisement, clinical and different program areas.

Principles of knowledge Mining explains and explores the critical thoughts of knowledge Mining: for class, organization rule mining and clustering. each one subject is obviously defined and illustrated by way of special labored examples, with a spotlight on algorithms instead of mathematical formalism. it's written for readers with out a robust historical past in arithmetic or information, and any formulae used are defined in detail.

This moment variation has been extended to incorporate extra chapters on utilizing common development timber for organization Rule Mining, evaluating classifiers, ensemble category and working with very huge volumes of data.

Principles of knowledge Mining goals to aid basic readers advance the mandatory knowing of what's contained in the 'black box' to allow them to use advertisement info mining applications discriminatingly, in addition to permitting complex readers or educational researchers to appreciate or give a contribution to destiny technical advances within the field.

Suitable as a textbook to aid classes at undergraduate or postgraduate degrees in quite a lot of matters together with desktop technology, enterprise stories, advertising and marketing, man made Intelligence, Bioinformatics and Forensic technology.

Download e-book for iPad: Data-ism: The Revolution Transforming Decision Making, by Steve Lohr

Steve Lohr, a know-how reporter for the hot York occasions, chronicles the increase of massive facts, addressing state-of-the-art enterprise recommendations and studying the darkish aspect of a data-driven international. Coal, iron ore, and oil have been the foremost efficient resources that fueled the commercial Revolution. this day, info is the important uncooked fabric of the knowledge economic system.

Additional resources for Advanced Methods for Knowledge Discovery from Complex Data

Sample text

S. and L. N. , 1986: Pattern Recognition in Practice II . North Holland, Amsterdam. , A. Srivastava, X. Yang and M. Sarrafzadeh, 2002: Optimal energy aware clustering in sensor networks. Sensors, 2, 258–69. Giles, C. , S. Lawrence and A. C. Tsoi, 2001: Noisy time series prediction using a recurrent neural network and grammatical inference. Machine Learning, 44, 161–83. , 2002: Efficient Frequent Pattern Mining. D. thesis, University of Limburg, Belgium. Goldberg, D. , 1989: Genetic Algorithms: Search, Optimization and Machine Learning.

GAs represent a form of multi-point, stochastic search in complex landscapes. Applications of genetic algorithms and related techniques in data mining include extraction of association rules [85], predictive rules [42, 43, 97], clustering [13, 15, 16, 91, 92, 93], program evolution [117, 126] and web mining [98, 99, 108, 109, 110]. 4 Recent Trends in Knowledge Discovery 31 the real world in a manner similar to biological systems. Their origin can be traced to the work of Hebb [57], where a local learning rule is proposed.

67] Jain, A. K. and R. C. Dubes, 1988: Algorithms for Clustering Data. Prentice-Hall, Englewood Cliffs, NJ. [68] 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. [70] Kargupta, H. and P. , 2001: Advances in Distributed and Parallel Knowledge Discovery. MIT Press. [71] Kargupta. H, R. Bhargava, K. Liu, M.

Download PDF sample

Advanced Methods for Knowledge Discovery from Complex Data by Ujjwal Maulik, Lawrence B. Holder, Diane J. Cook


by Charles
4.2

Rated 4.73 of 5 – based on 37 votes