Mining Complex Data
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Mining Complex Data
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Author : Zbigniew W. Ras
language : en
Publisher: Springer
Release Date : 2008-05-13
Mining Complex Data written by Zbigniew W. Ras and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-13 with Computers categories.
This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007. The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data. In contrast to the typical tabular data, complex data can consist of heterogenous data types, can come from different sources, or live in high dimensional spaces. All these specificities call for new data mining strategies.
Data Mining In Large Sets Of Complex Data
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Author : Robson Leonardo Ferreira Cordeiro
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-01-11
Data Mining In Large Sets Of Complex Data written by Robson Leonardo Ferreira Cordeiro and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-11 with Computers categories.
The amount and the complexity of the data gathered by current enterprises are increasing at an exponential rate. Consequently, the analysis of Big Data is nowadays a central challenge in Computer Science, especially for complex data. For example, given a satellite image database containing tens of Terabytes, how can we find regions aiming at identifying native rainforests, deforestation or reforestation? Can it be made automatically? Based on the work discussed in this book, the answers to both questions are a sound “yes”, and the results can be obtained in just minutes. In fact, results that used to require days or weeks of hard work from human specialists can now be obtained in minutes with high precision. Data Mining in Large Sets of Complex Data discusses new algorithms that take steps forward from traditional data mining (especially for clustering) by considering large, complex datasets. Usually, other works focus in one aspect, either data size or complexity. This work considers both: it enables mining complex data from high impact applications, such as breast cancer diagnosis, region classification in satellite images, assistance to climate change forecast, recommendation systems for the Web and social networks; the data are large in the Terabyte-scale, not in Giga as usual; and very accurate results are found in just minutes. Thus, it provides a crucial and well timed contribution for allowing the creation of real time applications that deal with Big Data of high complexity in which mining on the fly can make an immeasurable difference, such as supporting cancer diagnosis or detecting deforestation.
Mining Complex Data
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Author : Djamel A. Zighed
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-10-13
Mining Complex Data written by Djamel A. Zighed and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-13 with Mathematics categories.
The aim of this book is to gather the most recent works that address issues related to the concept of mining complex data. The whole knowledge discovery process being involved, our goal is to provide researchers dealing with each step of this process by key entries. Actually, managing complex data within the KDD process implies to work on every step, starting from the pre-processing (e.g. structuring and organizing) to the visualization and interpretation (e.g. sorting or filtering) of the results, via the data mining methods themselves (e.g. classification, clustering, frequent patterns extraction, etc.). The papers presented here are selected from the workshop papers held yearly since 2006.
Mining Complex Data
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Author : Zbigniew W. Ras
language : en
Publisher: Springer
Release Date : 2008-05-13
Mining Complex Data written by Zbigniew W. Ras and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-13 with Computers categories.
This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007. The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data. In contrast to the typical tabular data, complex data can consist of heterogenous data types, can come from different sources, or live in high dimensional spaces. All these specificities call for new data mining strategies.
New Frontiers In Mining Complex Patterns
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Author : Michelangelo Ceci
language : en
Publisher: Springer
Release Date : 2016-05-17
New Frontiers In Mining Complex Patterns written by Michelangelo Ceci and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-17 with Computers categories.
This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2015, held in conjunction with ECML-PKDD 2015 in Porto, Portugal, in September 2015. The 15 revised full papers presented together with one invited talk were carefully reviewed and selected from 19 submissions. They illustrate advanced data mining techniques which preserve the informative richness of complex data and allow for efficient and effective identification of complex information units present in such data. The papers are organized in the following sections: data stream mining, classification, mining complex data, and sequences.
Understanding Complex Datasets
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Author : David Skillicorn
language : en
Publisher: CRC Press
Release Date : 2007-05-17
Understanding Complex Datasets written by David Skillicorn and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-17 with Computers categories.
Making obscure knowledge about matrix decompositions widely available, Understanding Complex Datasets: Data Mining with Matrix Decompositions discusses the most common matrix decompositions and shows how they can be used to analyze large datasets in a broad range of application areas. Without having to understand every mathematical detail, the book
Cluster Effects In Mining Complex Data
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Author : M. Ishaq Bhatti
language : en
Publisher: Nova Science Publishers
Release Date : 2014-05-14
Cluster Effects In Mining Complex Data written by M. Ishaq Bhatti and has been published by Nova Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-14 with Cluster analysis categories.
Advanced Methods For Knowledge Discovery From Complex Data
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Author : Ujjwal Maulik
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-06
Advanced Methods For Knowledge Discovery From Complex Data written by Ujjwal Maulik and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-06 with Computers categories.
The growth in the amount of data collected and generated has exploded in recent times with the widespread automation of various day-to-day activities, advances in high-level scienti?c and engineering research and the development of e?cient data collection tools. This has given rise to the need for automa- callyanalyzingthedatainordertoextractknowledgefromit,therebymaking the data potentially more useful. Knowledge discovery and data mining (KDD) is the process of identifying valid, novel, potentially useful and ultimately understandable patterns from massive data repositories. It is a multi-disciplinary topic, drawing from s- eral ?elds including expert systems, machine learning, intelligent databases, knowledge acquisition, case-based reasoning, pattern recognition and stat- tics. Many data mining systems have typically evolved around well-organized database systems (e.g., relational databases) containing relevant information. But, more and more, one ?nds relevant information hidden in unstructured text and in other complex forms. Mining in the domains of the world-wide web, bioinformatics, geoscienti?c data, and spatial and temporal applications comprise some illustrative examples in this regard. Discovery of knowledge, or potentially useful patterns, from such complex data often requires the - plication of advanced techniques that are better able to exploit the nature and representation of the data. Such advanced methods include, among o- ers, graph-based and tree-based approaches to relational learning, sequence mining, link-based classi?cation, Bayesian networks, hidden Markov models, neural networks, kernel-based methods, evolutionary algorithms, rough sets and fuzzy logic, and hybrid systems. Many of these methods are developed in the following chapters.
Cluster Effects In Mining Complex Data
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Author : M. Ishaq Bhati
language : en
Publisher: Nova Science Publishers
Release Date : 2012
Cluster Effects In Mining Complex Data written by M. Ishaq Bhati and has been published by Nova Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Cluster analysis categories.
In the last few years, the tremendous growth in the use of clustered survey methods in data mining in the presence of cluster effects has dichotomised the subject of econometrics due to the nature and problems in the way the data is being gathered. This book develops and investigates diagnostic tests for such cluster effects. In addition, this book also considers several aspects of hypothesis testing problems associated with the testing for cluster effects using the multi-stage linear regression model. Throughout the book the principle of invariance is used to eliminate the nuisance parameters where possible, thus reducing the dimension of the testing problems
Complex Data Analytics With Formal Concept Analysis
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Author : Rokia Missaoui
language : en
Publisher: Springer Nature
Release Date : 2022-06-29
Complex Data Analytics With Formal Concept Analysis written by Rokia Missaoui and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-29 with Computers categories.
FCA is an important formalism that is associated with a variety of research areas such as lattice theory, knowledge representation, data mining, machine learning, and semantic Web. It is successfully exploited in an increasing number of application domains such as software engineering, information retrieval, social network analysis, and bioinformatics. Its mathematical power comes from its concept lattice formalization in which each element in the lattice captures a formal concept while the whole structure represents a conceptual hierarchy that offers browsing, clustering and association rule mining. Complex data analytics refers to advanced methods and tools for mining and analyzing data with complex structures such as XML/Json data, text and image data, multidimensional data, graphs, sequences and streaming data. It also covers visualization mechanisms used to highlight the discovered knowledge. This edited book examines a set of important and relevant research directions in complex data management, and updates the contribution of the FCA community in analyzing complex and large data such as knowledge graphs and interlinked contexts. For example, Formal Concept Analysis and some of its extensions are exploited, revisited and coupled with recent processing parallel and distributed paradigms to maximize the benefits in analyzing large data.