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Data Mining and Medical Knowledge Management: Cases and Applications
  • Language: en
  • Pages: 464

Data Mining and Medical Knowledge Management: Cases and Applications

  • Type: Book
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  • Published: 2009-02-28
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  • Publisher: IGI Global

The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.

Digital Libraries for Open Knowledge
  • Language: en
  • Pages: 404

Digital Libraries for Open Knowledge

  • Type: Book
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  • Published: 2018-09-04
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  • Publisher: Springer

This book constitutes the proceedings of the 22nd International Conference on Theory and Practice of Digital Libraries, TPDL 2018, held in Porto, Portugal, in September 2018. The 51 full papers, 17 short papers, and 13 poster and tutorial papers presented in this volume were carefully reviewed and selected from 81 submissions. The general theme of TPDL 2018 was Digital Libraries for Open Knowledge. The papers present a wide range of the following topics: Metadata, Entity Disambiguation, Data Management, Scholarly Communication, Digital Humanities, User Interaction, Resources, Information Extraction, Information Retrieval, Recommendation.

Advances in Knowledge Discovery and Data Mining, Part I
  • Language: en
  • Pages: 642

Advances in Knowledge Discovery and Data Mining, Part I

  • Type: Book
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  • Published: 2012-05-10
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  • Publisher: Springer

The two-volume set LNAI 7301 and 7302 constitutes the refereed proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2012, held in Kuala Lumpur, Malaysia, in May 2012. The total of 20 revised full papers and 66 revised short papers were carefully reviewed and selected from 241 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas. The papers are organized in topical sections on supervised learning: active, ensemble, rare-class and online; unsupervised learning: clustering, probabilistic modeling in the first volume and on pattern mining: networks, graphs, time-series and outlier detection, and data manipulation: pre-processing and dimension reduction in the second volume.

Advances in Knowledge Discovery and Data Mining, Part II
  • Language: en
  • Pages: 468

Advances in Knowledge Discovery and Data Mining, Part II

  • Type: Book
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  • Published: 2012-05-10
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  • Publisher: Springer

The two-volume set LNAI 7301 and 7302 constitutes the refereed proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2012, held in Kuala Lumpur, Malaysia, in May 2012. The total of 20 revised full papers and 66 revised short papers were carefully reviewed and selected from 241 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas. The papers are organized in topical sections on supervised learning: active, ensemble, rare-class and online; unsupervised learning: clustering, probabilistic modeling in the first volume and on pattern mining: networks, graphs, time-series and outlier detection, and data manipulation: pre-processing and dimension reduction in the second volume.

Advances in Knowledge Discovery and Management
  • Language: en
  • Pages: 340

Advances in Knowledge Discovery and Management

  • Type: Book
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  • Published: 2010-09-07
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  • Publisher: Springer

During the last decade, the French-speaking scientific community developed a very strong research activity in the field of Knowledge Discovery and Management (KDM or EGC for “Extraction et Gestion des Connaissances” in French), which is concerned with, among others, Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and SemanticWeb. The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC 2009 Conference held in Strasbourg, France on January 2009. The volume is organized in four parts. Part I includes five papers concerned by various aspects of supervised learning or information retrieval. Part II presents five papers concerned with unsupervised learning issues. Part III includes two papers on data streaming and two on security while in Part IV the last four papers are concerned with ontologies and semantic.

Database and Expert Systems Applications
  • Language: en
  • Pages: 974

Database and Expert Systems Applications

  • Type: Book
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  • Published: 2005-09-14
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  • Publisher: Springer

DEXA 2005, the 16th International Conference on Database and Expert Systems Applications, was held at the Copenhagen Business School, Copenhagen, Denmark, from August 22 to 26, 2005. The success of the DEXA series has partly been due to the way in which it has kept abreast of recent developments by spawning specialized workshops and conferences each with its own proceedings. In 2005 the DEXA programme was co-located with the 7th International Conference on Data Warehousing and Knowledge Discovery [DaWaK 2005], the 6th International Conference on Electronic Commerce and Web Technologies [EC-Web 2005], the 4th International Conference on Electronic Government [EGOV 2005], the 2nd International...

Selected Contributions in Data Analysis and Classification
  • Language: en
  • Pages: 619

Selected Contributions in Data Analysis and Classification

This volume presents recent methodological developments in data analysis and classification. It covers a wide range of topics, including methods for classification and clustering, dissimilarity analysis, consensus methods, conceptual analysis of data, and data mining and knowledge discovery in databases. The book also presents a wide variety of applications, in fields such as biology, micro-array analysis, cyber traffic, and bank fraud detection.

Complex-Valued Neural Networks
  • Language: en
  • Pages: 205

Complex-Valued Neural Networks

  • Type: Book
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  • Published: 2012-03-22
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  • Publisher: Springer

This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks a...

Data Warehousing and Knowledge Discovery
  • Language: en
  • Pages: 497

Data Warehousing and Knowledge Discovery

This book constitutes the refereed proceedings of the 8th International Conference on Data Warehousing and Knowledge Discovery, DaWak 2007, held in Regensburg, Germany, September 2007. Coverage includes ETL processing, multidimensional design, OLAP and multidimensional model, cubes processing, data warehouse applications, frequent itemsets, ontology-based mining, clustering, association rules, miscellaneous applications, and classification.

Beyond Quantity
  • Language: en
  • Pages: 361

Beyond Quantity

How do artificial neural networks and other forms of artificial intelligence interfere with methods and practices in the sciences? Which interdisciplinary epistemological challenges arise when we think about the use of AI beyond its dependency on big data? Not only the natural sciences, but also the social sciences and the humanities seem to be increasingly affected by current approaches of subsymbolic AI, which master problems of quality (fuzziness, uncertainty) in a hitherto unknown way. But what are the conditions, implications, and effects of these (potential) epistemic transformations and how must research on AI be configured to address them adequately?