Mining Of Data With Complex Structures

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Mining of Data with Complex Structures

Fedja Hadzic,Henry Tan,Tharam S. Dillon
Mining of Data with Complex Structures Book PDF

Author : Fedja Hadzic,Henry Tan,Tharam S. Dillon
Publisher : Springer
Page : 328 pages
File Size : 41,6 Mb
Release : 2011-02-03
Category : Computers
ISBN : 9783642175572

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Mining of Data with Complex Structures by Fedja Hadzic,Henry Tan,Tharam S. Dillon Pdf

Mining of Data with Complex Structures: - Clarifies the type and nature of data with complex structure including sequences, trees and graphs - Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining. - Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints. - Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.) - Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees. - Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees. - Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach. - Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies. - Details the extension of the TMG framework for sequence mining - Provides an overview of the future research direction with respect to technical extensions and application areas The primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry. In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains.

Data Mining

Jiawei Han,Micheline Kamber
Data Mining Book PDF

Author : Jiawei Han,Micheline Kamber
Publisher : Unknown
Page : 703 pages
File Size : 49,6 Mb
Release : 2012
Category : Artificial intelligence
ISBN : 9380931913

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Data Mining by Jiawei Han,Micheline Kamber Pdf

Mining of Data with Complex Structures explores nature of data with complex structure including sequences, trees and graphs. Readers will find a detailed description of the state-of-the-art of sequence mining, tree mining and graph mining, and more.

Data Mining

Jiawei Han,Micheline Kamber
Data Mining Book PDF

Author : Jiawei Han,Micheline Kamber
Publisher : Unknown
Page : 0 pages
File Size : 49,8 Mb
Release : 2012
Category : Algorithms
ISBN : 9380931913

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Data Mining by Jiawei Han,Micheline Kamber Pdf

Mining of Data with Complex Structures explores nature of data with complex structure including sequences, trees and graphs. Readers will find a detailed description of the state-of-the-art of sequence mining, tree mining and graph mining, and more.

Complex Data Analytics with Formal Concept Analysis

Rokia Missaoui,Léonard Kwuida,Talel Abdessalem
Complex Data Analytics with Formal Concept Analysis Book PDF

Author : Rokia Missaoui,Léonard Kwuida,Talel Abdessalem
Publisher : Springer Nature
Page : 277 pages
File Size : 40,5 Mb
Release : 2022-06-29
Category : Computers
ISBN : 9783030932787

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Complex Data Analytics with Formal Concept Analysis by Rokia Missaoui,Léonard Kwuida,Talel Abdessalem Pdf

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.

Understanding Complex Datasets

David Skillicorn
Understanding Complex Datasets Book PDF

Author : David Skillicorn
Publisher : CRC Press
Page : 268 pages
File Size : 44,8 Mb
Release : 2007-05-17
Category : Computers
ISBN : 9781584888338

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Understanding Complex Datasets by David Skillicorn Pdf

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

Mining Complex Data

Zbigniew W. Ras,Shusaku Tsumoto,Djamel A. Zighed
Mining Complex Data Book PDF

Author : Zbigniew W. Ras,Shusaku Tsumoto,Djamel A. Zighed
Publisher : Springer
Page : 265 pages
File Size : 48,7 Mb
Release : 2008-05-13
Category : Computers
ISBN : 9783540684169

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Mining Complex Data by Zbigniew W. Ras,Shusaku Tsumoto,Djamel A. Zighed Pdf

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 the Web

Zdravko Markov,Daniel T. Larose
Data Mining the Web Book PDF

Author : Zdravko Markov,Daniel T. Larose
Publisher : John Wiley & Sons
Page : 236 pages
File Size : 47,5 Mb
Release : 2007-04-06
Category : Computers
ISBN : 9780470108086

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Data Mining the Web by Zdravko Markov,Daniel T. Larose Pdf

This book introduces the reader to methods of data mining on the web, including uncovering patterns in web content (classification, clustering, language processing), structure (graphs, hubs, metrics), and usage (modeling, sequence analysis, performance).

Data Mining and Knowledge Discovery for Big Data

Wesley W. Chu
Data Mining and Knowledge Discovery for Big Data Book PDF

Author : Wesley W. Chu
Publisher : Springer Science & Business Media
Page : 314 pages
File Size : 54,9 Mb
Release : 2013-09-24
Category : Technology & Engineering
ISBN : 9783642408373

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Data Mining and Knowledge Discovery for Big Data by Wesley W. Chu Pdf

The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease. Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation. The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.

Mining Latent Entity Structures

Chi Wang,Jiawei Han
Mining Latent Entity Structures Book PDF

Author : Chi Wang,Jiawei Han
Publisher : Springer Nature
Page : 147 pages
File Size : 40,9 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031019074

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Mining Latent Entity Structures by Chi Wang,Jiawei Han Pdf

The "big data" era is characterized by an explosion of information in the form of digital data collections, ranging from scientific knowledge, to social media, news, and everyone's daily life. Examples of such collections include scientific publications, enterprise logs, news articles, social media, and general web pages. Valuable knowledge about multi-typed entities is often hidden in the unstructured or loosely structured, interconnected data. Mining latent structures around entities uncovers hidden knowledge such as implicit topics, phrases, entity roles and relationships. In this monograph, we investigate the principles and methodologies of mining latent entity structures from massive unstructured and interconnected data. We propose a text-rich information network model for modeling data in many different domains. This leads to a series of new principles and powerful methodologies for mining latent structures, including (1) latent topical hierarchy, (2) quality topical phrases, (3) entity roles in hierarchical topical communities, and (4) entity relations. This book also introduces applications enabled by the mined structures and points out some promising research directions.

Mining Complex Data

Djamel A. Zighed,Shusaku Tsumoto,Zbigniew W. Ras,Hakim Hacid
Mining Complex Data Book PDF

Author : Djamel A. Zighed,Shusaku Tsumoto,Zbigniew W. Ras,Hakim Hacid
Publisher : Springer
Page : 302 pages
File Size : 48,5 Mb
Release : 2008-10-10
Category : Technology & Engineering
ISBN : 9783540880677

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Mining Complex Data by Djamel A. Zighed,Shusaku Tsumoto,Zbigniew W. Ras,Hakim Hacid Pdf

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.

Intelligent Data Engineering and Automated Learning -- IDEAL 2012

Hujun Yin,Jose A.F. Costa,Guilherme Barreto
Intelligent Data Engineering and Automated Learning IDEAL 2012 Book PDF

Author : Hujun Yin,Jose A.F. Costa,Guilherme Barreto
Publisher : Springer
Page : 882 pages
File Size : 47,8 Mb
Release : 2012-08-01
Category : Computers
ISBN : 9783642326394

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Intelligent Data Engineering and Automated Learning -- IDEAL 2012 by Hujun Yin,Jose A.F. Costa,Guilherme Barreto Pdf

This book constitutes the refereed proceedings of the 13th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2012, held in Natal, Brazil, in August 2012. The 100 revised full papers presented were carefully reviewed and selected from more than 200 submissions for inclusion in the book and present the latest theoretical advances and real-world applications in computational intelligence.

Mining Multimedia and Complex Data

Osmar R. Zaiane,Simeon Simoff,Chabane Djeraba
Mining Multimedia and Complex Data Book PDF

Author : Osmar R. Zaiane,Simeon Simoff,Chabane Djeraba
Publisher : Springer
Page : 284 pages
File Size : 55,8 Mb
Release : 2003-10-23
Category : Computers
ISBN : 9783540396666

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Mining Multimedia and Complex Data by Osmar R. Zaiane,Simeon Simoff,Chabane Djeraba Pdf

1 WorkshopTheme Digital multimedia di?ers from previous forms of combined media in that the bits that represent text, images, animations, and audio, video and other signals can be treated as data by computer programs. One facet of this diverse data in termsofunderlyingmodelsandformatsisthatitissynchronizedandintegrated, hence it can be treated as integral data records. Such records can be found in a number of areas of human endeavour. Modern medicine generates huge amounts of such digital data. Another - ample is architectural design and the related architecture, engineering and c- struction (AEC) industry. Virtual communities (in the broad sense of this word, which includes any communities mediated by digital technologies) are another example where generated data constitutes an integral data record. Such data may include data about member pro?les, the content generated by the virtual community, and communication data in di?erent formats, including e-mail, chat records, SMS messages, videoconferencing records. Not all multimedia data is so diverse. An example of less diverse data, but data that is larger in terms of the collected amount, is that generated by video surveillance systems, where each integral data record roughly consists of a set of time-stamped images – the video frames. In any case, the collection of such in- gral data records constitutes a multimedia data set. The challenge of extracting meaningful patterns from such data sets has led to the research and devel- ment in the area of multimedia data mining.

Complex Pattern Mining

Annalisa Appice,Michelangelo Ceci,Corrado Loglisci,Giuseppe Manco,Elio Masciari,Zbigniew W. Ras
Complex Pattern Mining Book PDF

Author : Annalisa Appice,Michelangelo Ceci,Corrado Loglisci,Giuseppe Manco,Elio Masciari,Zbigniew W. Ras
Publisher : Springer Nature
Page : 251 pages
File Size : 50,5 Mb
Release : 2020-01-14
Category : Technology & Engineering
ISBN : 9783030366179

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Complex Pattern Mining by Annalisa Appice,Michelangelo Ceci,Corrado Loglisci,Giuseppe Manco,Elio Masciari,Zbigniew W. Ras Pdf

This book discusses the challenges facing current research in knowledge discovery and data mining posed by the huge volumes of complex data now gathered in various real-world applications (e.g., business process monitoring, cybersecurity, medicine, language processing, and remote sensing). The book consists of 14 chapters covering the latest research by the authors and the research centers they represent. It illustrates techniques and algorithms that have recently been developed to preserve the richness of the data and allow us to efficiently and effectively identify the complex information it contains. Presenting the latest developments in complex pattern mining, this book is a valuable reference resource for data science researchers and professionals in academia and industry.

Data-Centric Structural Health Monitoring

Mohammad Noori,Fuh-Gwo Yuan,Ehsan Noroozinejad Farsangi
Data Centric Structural Health Monitoring Book PDF

Author : Mohammad Noori,Fuh-Gwo Yuan,Ehsan Noroozinejad Farsangi
Publisher : Walter de Gruyter GmbH & Co KG
Page : 359 pages
File Size : 47,8 Mb
Release : 2023-09-04
Category : Technology & Engineering
ISBN : 9783110791518

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Data-Centric Structural Health Monitoring by Mohammad Noori,Fuh-Gwo Yuan,Ehsan Noroozinejad Farsangi Pdf

This book introduces the latest developments in data-centric engineering, including different artificial intelligence and machine learning schemes, as well as their wide range of applications for long-term monitoring and health assessment of mechanical, aerospace and complex infrastructure systems. Leading scholars in the field show how these emerging techniques assure the longevity of engineered systems and predict their life cycles.

Semantic Data Mining

A. Ławrynowicz
Semantic Data Mining Book PDF

Author : A. Ławrynowicz
Publisher : IOS Press
Page : 210 pages
File Size : 40,6 Mb
Release : 2017-04-18
Category : Computers
ISBN : 9781614997467

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Semantic Data Mining by A. Ławrynowicz Pdf

Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research and industry. The book is devoted to semantic data mining – a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies and knowledge graphs, rather than only purely empirical data. The introductory chapters of the book provide theoretical foundations of both data mining and ontology representation. Taking a unified perspective, the book then covers several methods for semantic data mining, addressing tasks such as pattern mining, classification and similarity-based approaches. It attempts to provide state-of-the-art answers to specific challenges and peculiarities of data mining with use of ontologies, in particular: How to deal with incompleteness of knowledge and the so-called Open World Assumption? What is a truly “semantic” similarity measure? The book contains several chapters with examples of applications of semantic data mining. The examples start from a scenario with moderate use of lightweight ontologies for knowledge graph enrichment and end with a full-fledged scenario of an intelligent knowledge discovery assistant using complex domain ontologies for meta-mining, i.e., an ontology-based meta-learning approach to full data mining processes. The book is intended for researchers in the fields of semantic technologies, knowledge engineering, data science, and data mining, and developers of knowledge-based systems and applications.