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Principles of Data Mining and Knowledge Discovery

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Cover of 'Principles of Data Mining and Knowledge Discovery'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Scaling up Dynamic Time Warping to Massive Datasets
  3. Altmetric Badge
    Chapter 2 The Haar Wavelet Transform in the Time Series Similarity Paradigm
  4. Altmetric Badge
    Chapter 3 Rule Discovery in Large Time-Series Medical Databases
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    Chapter 4 Simultaneous Prediction of Multiple Chemical Parameters of River Water Quality with TILDE
  6. Altmetric Badge
    Chapter 5 Applying Data Mining Techniques to Wafer Manufacturing
  7. Altmetric Badge
    Chapter 6 An Application of Data Mining to the Problem of the University Students’ Dropout Using Markov Chains
  8. Altmetric Badge
    Chapter 7 Discovering and Visualizing Attribute Associations Using Bayesian Networks and Their Use in KDD
  9. Altmetric Badge
    Chapter 8 Taxonomy Formation by Approximate Equivalence Relations, Revisited
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    Chapter 9 On the Use of Self-Organizing Maps for Clustering and Visualization
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    Chapter 10 Speeding Up the Search for Optimal Partitions
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    Chapter 11 Experiments in Meta-level Learning with ILP
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    Chapter 12 Boolean Reasoning Scheme with Some Applications in Data Mining
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    Chapter 13 On the Correspondence between Classes of Implicational and Equivalence Quantifiers
  15. Altmetric Badge
    Chapter 14 Querying Inductive Databases via Logic-Based User-Defined Aggregates
  16. Altmetric Badge
    Chapter 15 Peculiarity Oriented Multi-database Mining
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    Chapter 16 Knowledge Discovery in Medical Multi-databases: A Rough Set Approach
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    Chapter 17 Automated Discovery of Rules and Exceptions from Distributed Databases Using Aggregates
  19. Altmetric Badge
    Chapter 18 Text Mining via Information Extraction
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    Chapter 19 TopCat: Data Mining for Topic Identification in a Text Corpus
  21. Altmetric Badge
    Chapter 20 Selection and Statistical Validation of Features and Prototypes
  22. Altmetric Badge
    Chapter 21 Taming Large Rule Models in Rough Set Approaches
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    Chapter 22 Optimizing Disjunctive Association Rules
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    Chapter 23 Contribution of Boosting in Wrapper Models
  25. Altmetric Badge
    Chapter 24 Experiments on a Representation-Independent “Top-Down and Prune” Induction Scheme
  26. Altmetric Badge
    Chapter 25 Heuristic Measures of Interestingness
  27. Altmetric Badge
    Chapter 26 Enhancing Rule Interestingness for Neuro-fuzzy Systems
  28. Altmetric Badge
    Chapter 27 Unsupervised Profiling for Identifying Superimposed Fraud
  29. Altmetric Badge
    Chapter 28 OPTICS-OF: Identifying Local Outliers
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    Chapter 29 Selective Propositionalization for Relational Learning
  31. Altmetric Badge
    Chapter 30 Circle Graphs: New Visualization Tools for Text-Mining
  32. Altmetric Badge
    Chapter 31 On the Consistency of Information Filters for Lazy Learning Algorithms
  33. Altmetric Badge
    Chapter 32 Using Genetic Algorithms to Evolve a Rule Hierarchy
  34. Altmetric Badge
    Chapter 33 Mining Temporal Features in Association Rules
  35. Altmetric Badge
    Chapter 34 The Improvement of Response Modeling: Combining Rule-Induction and Case-Based Reasoning
  36. Altmetric Badge
    Chapter 35 Analyzing an Email Collection Using Formal Concept Analysis
  37. Altmetric Badge
    Chapter 36 Business Focused Evaluation Methods: A Case Study
  38. Altmetric Badge
    Chapter 37 Combining Data and Knowledge by MaxEnt-Optimization of Probability Distributions
  39. Altmetric Badge
    Chapter 38 Handling Missing Data in Trees: Surrogate Splits or Statistical Imputation?
  40. Altmetric Badge
    Chapter 39 Rough Dependencies as a Particular Case of Correlation: Application to the Calculation of Approximative Reducts
  41. Altmetric Badge
    Chapter 40 A Fuzzy Beam-Search Rule Induction Algorithm
  42. Altmetric Badge
    Chapter 41 An Innovative GA-Based Decision Tree Classifier in Large Scale Data Mining
  43. Altmetric Badge
    Chapter 42 Extension to C-means Algorithm for the Use of Similarity Functions
  44. Altmetric Badge
    Chapter 43 Predicting Chemical Carcinogenesis Using Structural Information Only
  45. Altmetric Badge
    Chapter 44 LA – A Clustering Algorithm with an Automated Selection of Attributes, Which is Invariant to Functional Transformations of Coordinates
  46. Altmetric Badge
    Chapter 45 Association Rule Selection in a Data Mining Environment
  47. Altmetric Badge
    Chapter 46 Multi-relational Decision Tree Induction
  48. Altmetric Badge
    Chapter 47 Learning of Simple Conceptual Graphs from Positive and Negative Examples
  49. Altmetric Badge
    Chapter 48 An Evolutionary Algorithm Using Multivariate Discretization for Decision Rule Induction
  50. Altmetric Badge
    Chapter 49 ZigZag, a New Clustering Algorithm to Analyze Categorical Variable Cross-Classification Tables
  51. Altmetric Badge
    Chapter 50 Efficient Mining of High Confidence Association Rules without Support Thresholds
  52. Altmetric Badge
    Chapter 51 A Logical Approach to Fuzzy Data Analysis
  53. Altmetric Badge
    Chapter 52 AST: Support for Algorithm Selection with a CBR Approach
  54. Altmetric Badge
    Chapter 53 Efficient Shared Near Neighbours Clustering of Large Metric Data Sets
  55. Altmetric Badge
    Chapter 54 Discovery of “Interesting” Data Dependencies from a Workload of SQL Statements
  56. Altmetric Badge
    Chapter 55 Learning from Highly Structured Data by Decomposition
  57. Altmetric Badge
    Chapter 56 Combinatorial Approach for Data Binarization
  58. Altmetric Badge
    Chapter 57 Extending Attribute-Oriented Induction as a Key-Preserving Data Mining Method
  59. Altmetric Badge
    Chapter 58 Automated Discovery of Polynomials by Inductive Genetic Programming
  60. Altmetric Badge
    Chapter 59 Diagnosing Acute Appendicitis with Very Simple Classification Rules
  61. Altmetric Badge
    Chapter 60 Rule Induction in Cascade Model Based on Sum of Squares Decomposition
  62. Altmetric Badge
    Chapter 61 Maintenance of Discovered Knowledge
  63. Altmetric Badge
    Chapter 62 A Divisive Initialisation Method for Clustering Algorithms
  64. Altmetric Badge
    Chapter 63 A Comparison of Model Selection Procedures for Predicting Turning Points in Financial Time Series
  65. Altmetric Badge
    Chapter 64 Mining Lemma Disambiguation Rules from Czech Corpora
  66. Altmetric Badge
    Chapter 65 Adding Temporal Semantics to Association Rules
  67. Altmetric Badge
    Chapter 66 Studying the Behavior of Generalized Entropy in Induction Trees Using a M-of-N Concept
  68. Altmetric Badge
    Chapter 67 Discovering Rules in Information Trees
  69. Altmetric Badge
    Chapter 68 Mining Text Archives: Creating Readable Maps to Structure and Describe Document Collections
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    Chapter 69 Neuro-fuzzy Data Mining for Target Group Selection in Retail Banking
  71. Altmetric Badge
    Chapter 70 Mining Possibilistic Set-Valued Rules by Generating Prime Disjunctions
  72. Altmetric Badge
    Chapter 71 Towards Discovery of Information Granules
  73. Altmetric Badge
    Chapter 72 Classification Algorithms Based on Linear Combinations of Features
  74. Altmetric Badge
    Chapter 73 Managing Interesting Rules in Sequence Mining
  75. Altmetric Badge
    Chapter 74 Support Vector Machines for Knowledge Discovery
  76. Altmetric Badge
    Chapter 75 Regression by Feature Projections
  77. Altmetric Badge
    Chapter 76 Generating Linguistic Fuzzy Rules for Pattern Classification with Genetic Algorithms
  78. Altmetric Badge
    Chapter 77 Data Mining for Robust Business Intelligence Solutions
  79. Altmetric Badge
    Chapter 78 Query Languages for Knowledge Discovery in Databases
  80. Altmetric Badge
    Chapter 79 The ESPRIT Project CreditMine and its Relevance for the Internet Market
  81. Altmetric Badge
    Chapter 80 Logics and Statistics for Association Rules and Beyond
  82. Altmetric Badge
    Chapter 81 Data Mining for the Web
  83. Altmetric Badge
    Chapter 82 Relational Learning and Inductive Logic Programming Made Easy
Attention for Chapter 28: OPTICS-OF: Identifying Local Outliers
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Mentioned by

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Citations

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Readers on

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Chapter title
OPTICS-OF: Identifying Local Outliers
Chapter number 28
Book title
Principles of Data Mining and Knowledge Discovery
Published in
Lecture notes in computer science, September 1999
DOI 10.1007/978-3-540-48247-5_28
Book ISBNs
978-3-54-066490-1, 978-3-54-048247-5
Authors

Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng, Jörg Sander, Breunig, Markus M., Kriegel, Hans-Peter, Ng, Raymond T., Sander, Jörg

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 142 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 3%
Ireland 1 <1%
Brazil 1 <1%
India 1 <1%
Cyprus 1 <1%
Mexico 1 <1%
Canada 1 <1%
Japan 1 <1%
Korea, Republic of 1 <1%
Other 0 0%
Unknown 130 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 42 30%
Student > Master 33 23%
Researcher 18 13%
Student > Bachelor 12 8%
Other 6 4%
Other 19 13%
Unknown 12 8%
Readers by discipline Count As %
Computer Science 79 56%
Engineering 20 14%
Business, Management and Accounting 4 3%
Biochemistry, Genetics and Molecular Biology 4 3%
Physics and Astronomy 4 3%
Other 14 10%
Unknown 17 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 March 2024.
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#7,454,427
of 22,789,566 outputs
Outputs from Lecture notes in computer science
#2,486
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Outputs of similar age
#11,090
of 34,700 outputs
Outputs of similar age from Lecture notes in computer science
#6
of 17 outputs
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We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.