Knowledge Discovery and Data Mining: The Info-Fuzzy Network (IFN) Methodology
This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer US
2001
|
| Ausgabe: | 1st ed. 2001 |
| Schriftenreihe: | Massive Computing
1 |
| Schlagworte: | |
| Online-Zugang: | UBY01 Volltext |
| Zusammenfassung: | This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http://www.eng.tau.ac.iV-maimonlifn-kdg£). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results) |
| Beschreibung: | 1 Online-Ressource (XVIII, 168 p) |
| ISBN: | 9781475732962 |
| DOI: | 10.1007/978-1-4757-3296-2 |
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| 490 | 0 | |a Massive Computing |v 1 | |
| 520 | |a This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http://www.eng.tau.ac.iV-maimonlifn-kdg£). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results) | ||
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| discipline | Informatik |
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| edition | 1st ed. 2001 |
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| spelling | Maimon, O. Verfasser aut Knowledge Discovery and Data Mining The Info-Fuzzy Network (IFN) Methodology by O. Maimon, M. Last 1st ed. 2001 New York, NY Springer US 2001 1 Online-Ressource (XVIII, 168 p) txt rdacontent c rdamedia cr rdacarrier Massive Computing 1 This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http://www.eng.tau.ac.iV-maimonlifn-kdg£). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results) Data Structures and Information Theory Artificial Intelligence Coding and Information Theory Mathematical Logic and Foundations Statistics, general Data structures (Computer science) Artificial intelligence Coding theory Information theory Mathematical logic Statistics Last, M. aut Erscheint auch als Druck-Ausgabe 9781441948427 Erscheint auch als Druck-Ausgabe 9780792366478 Erscheint auch als Druck-Ausgabe 9781475732979 https://doi.org/10.1007/978-1-4757-3296-2 Verlag URL des Eerstveröffentlichers Volltext |
| spellingShingle | Maimon, O. Last, M. Knowledge Discovery and Data Mining The Info-Fuzzy Network (IFN) Methodology Data Structures and Information Theory Artificial Intelligence Coding and Information Theory Mathematical Logic and Foundations Statistics, general Data structures (Computer science) Artificial intelligence Coding theory Information theory Mathematical logic Statistics |
| title | Knowledge Discovery and Data Mining The Info-Fuzzy Network (IFN) Methodology |
| title_auth | Knowledge Discovery and Data Mining The Info-Fuzzy Network (IFN) Methodology |
| title_exact_search | Knowledge Discovery and Data Mining The Info-Fuzzy Network (IFN) Methodology |
| title_exact_search_txtP | Knowledge Discovery and Data Mining The Info-Fuzzy Network (IFN) Methodology |
| title_full | Knowledge Discovery and Data Mining The Info-Fuzzy Network (IFN) Methodology by O. Maimon, M. Last |
| title_fullStr | Knowledge Discovery and Data Mining The Info-Fuzzy Network (IFN) Methodology by O. Maimon, M. Last |
| title_full_unstemmed | Knowledge Discovery and Data Mining The Info-Fuzzy Network (IFN) Methodology by O. Maimon, M. Last |
| title_short | Knowledge Discovery and Data Mining |
| title_sort | knowledge discovery and data mining the info fuzzy network ifn methodology |
| title_sub | The Info-Fuzzy Network (IFN) Methodology |
| topic | Data Structures and Information Theory Artificial Intelligence Coding and Information Theory Mathematical Logic and Foundations Statistics, general Data structures (Computer science) Artificial intelligence Coding theory Information theory Mathematical logic Statistics |
| topic_facet | Data Structures and Information Theory Artificial Intelligence Coding and Information Theory Mathematical Logic and Foundations Statistics, general Data structures (Computer science) Artificial intelligence Coding theory Information theory Mathematical logic Statistics |
| url | https://doi.org/10.1007/978-1-4757-3296-2 |
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