Advances in Knowledge Discovery and Management: Volume 6 by Fabrice Guillet, Bruno Pinaud, Gilles Venturini

By Fabrice Guillet, Bruno Pinaud, Gilles Venturini

This booklet provides a set of consultant and novel paintings within the box of information mining, wisdom discovery, clustering and class, according to improved and remodeled types of a range of the simplest papers initially provided in French on the EGC 2014 and EGC 2015 meetings held in Rennes (France) in January 2014 and Luxembourg in January 2015. The e-book is in 3 components: the 1st 4 chapters speak about optimization issues in information mining. the second one half explores particular caliber measures, dissimilarities and ultrametrics. the ultimate chapters specialise in semantics, ontologies and social networks.
Written for PhD and MSc scholars, in addition to researchers operating within the box, it addresses either theoretical and sensible elements of data discovery and management.

Show description

Read or Download Advances in Knowledge Discovery and Management: Volume 6 PDF

Similar data mining books

Machine Learning: The Art and Science of Algorithms that Make Sense of Data

As essentially the most entire computer studying texts round, this e-book does justice to the field's fabulous richness, yet with out wasting sight of the unifying rules. Peter Flach's transparent, example-based strategy starts by means of discussing how a junk mail clear out works, which provides a right away advent to computing device studying in motion, with at least technical fuss.

Fuzzy logic, identification, and predictive control

The complexity and sensitivity of recent commercial procedures and platforms more and more require adaptable complicated regulate protocols. those controllers must be capable of take care of situations not easy ôjudgementö instead of basic ôyes/noö, ôon/offö responses, conditions the place an vague linguistic description is usually extra appropriate than a cut-and-dried numerical one.

Data Clustering in C++: An Object-Oriented Approach

Facts clustering is a hugely interdisciplinary box, the target of that's to divide a collection of items into homogeneous teams such that gadgets within the comparable staff are comparable and gadgets in numerous teams are really distinctive. millions of theoretical papers and a couple of books on info clustering were released during the last 50 years.

Fifty Years of Fuzzy Logic and its Applications

Entire and well timed file on fuzzy good judgment and its applications
Analyzes the paradigm shift in uncertainty administration upon the creation of fuzzy logic
Edited and written by way of best scientists in either theoretical and utilized fuzzy logic

This e-book provides a accomplished document at the evolution of Fuzzy good judgment for the reason that its formula in Lotfi Zadeh’s seminal paper on “fuzzy sets,” released in 1965. moreover, it includes a stimulating sampling from the vast box of analysis and improvement encouraged by way of Zadeh’s paper. The chapters, written by means of pioneers and favourite students within the box, exhibit how fuzzy units were effectively utilized to synthetic intelligence, keep an eye on thought, inference, and reasoning. The ebook additionally stories on theoretical matters; gains contemporary purposes of Fuzzy good judgment within the fields of neural networks, clustering, info mining and software program checking out; and highlights a major paradigm shift brought on by Fuzzy common sense within the sector of uncertainty administration. Conceived via the editors as an instructional occasion of the fifty years’ anniversary of the 1965 paper, this paintings is a must have for college kids and researchers keen to get an inspiring photograph of the possibilities, barriers, achievements and accomplishments of Fuzzy Logic-based systems.

Computational Intelligence
Data Mining and information Discovery
Artificial Intelligence (incl. Robotics)

Additional info for Advances in Knowledge Discovery and Management: Volume 6

Sample text

Such databases open new challenges for assessing the robustness and generalization capabilities of gesture recognition algorithms on diversified motion data sets. Besides the quality of recognition, the complexity of the algorithms and their computational cost is indeed a major issue, especially in the context of real-time interaction. We address in this paper the recognition of isolated gestures from motion captured data.

In International Joint Conference on Neural Network Proceedings (pp. 1680–1688). Boullé, M. (2007a). Compression-based averaging of selective naive bayes classifiers. Journal of Machine Learning Research, 8, 1659–1685. Boullé, M. (2007b). Recherche d’une représentation des données efficace pour la fouille des grandes bases de données. PhD thesis, Ecole Nationale Supérieure des Télécommunications. , & Xiao, L. (2012). Optimal distributed online prediction using mini-batches. Journal of Machine Learning Research, 13(1), 165–202.

To 3, 4, 5. For a VNS metaheuristic, the train compression rate is significantly improved for resp. 18, 19, 23 of the 36 datasets with an optimization level equal resp. to 3, 4, 5. The VNS metaheuristic seems then better than the MS metaheuristic: the guided exploration within a variable sized neighborhood from the best minimum encountered enables a more fruitful exploration than a purely random exploration. Figure 3 illustrates this iterations “waste” phenomenon with multi-start at the beginning of each start.

Download PDF sample

Rated 4.93 of 5 – based on 49 votes