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Advanced Methods for Knowledge Discovery from Complex Data
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
Knowledge Discovery and Data Mining
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Chapter 2
Automatic Discovery of Class Hierarchies via Output Space Decomposition
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Chapter 3
Graph-based Mining of Complex Data
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Chapter 4
Predictive Graph Mining with Kernel Methods
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Chapter 5
TreeMiner : An Efficient Algorithm for Mining Embedded Ordered Frequent Trees
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Chapter 6
Sequence Data Mining
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Chapter 7
Link-based Classification
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Chapter 8
Knowledge Discovery from Evolutionary Trees
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Chapter 9
Ontology-Assisted Mining of RDF Documents
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Chapter 10
Image Retrieval using Visual Features and Relevance Feedback
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Chapter 11
Significant Feature Selection Using Computational Intelligent Techniques for Intrusion Detection
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Chapter 12
On-board Mining of Data Streams in Sensor Networks
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Chapter 13
Discovering an Evolutionary Classifier over a High-speed Nonstatic Stream
Overall attention for this book and its chapters
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Mentioned by
syllabi
1
institution with syllabi
Citations
dimensions_citation
13
Dimensions
Readers on
mendeley
55
Mendeley
Book overview
1. Knowledge Discovery and Data Mining
2. Automatic Discovery of Class Hierarchies via Output Space Decomposition
3. Graph-based Mining of Complex Data
4. Predictive Graph Mining with Kernel Methods
5. TreeMiner : An Efficient Algorithm for Mining Embedded Ordered Frequent Trees
6. Sequence Data Mining
7. Link-based Classification
8. Knowledge Discovery from Evolutionary Trees
9. Ontology-Assisted Mining of RDF Documents
10. Image Retrieval using Visual Features and Relevance Feedback
11. Significant Feature Selection Using Computational Intelligent Techniques for Intrusion Detection
12. On-board Mining of Data Streams in Sensor Networks
13. Discovering an Evolutionary Classifier over a High-speed Nonstatic Stream
Summary
Syllabi
Dimensions citations
This data is correct as of December 2015 - for more up to date information, please visit
https://opensyllabus.org/
So far, Altmetric has seen this research output assigned in
1
syllabus from an institution on Open Syllabus Project.
Institution
Syllabi count
Course subject areas covered
Unknown
1
Business, Engineering, Biology, History, Law