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Principles of Data Mining and Knowledge Discovery

Overview of attention for book
Cover of 'Principles of Data Mining and Knowledge Discovery'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Optimized Substructure Discovery for Semi-structured Data
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    Chapter 2 Fast Outlier Detection in High Dimensional Spaces
  4. Altmetric Badge
    Chapter 3 Data Mining in Schizophrenia Research — Preliminary Analysis
  5. Altmetric Badge
    Chapter 4 Fast Algorithms for Mining Emerging Patterns
  6. Altmetric Badge
    Chapter 5 On the Discovery of Weak Periodicities in Large Time Series
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    Chapter 6 The Need for Low Bias Algorithms in Classification Learning from Large Data Sets
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    Chapter 7 Mining All Non-derivable Frequent Itemsets
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    Chapter 8 Iterative Data Squashing for Boosting Based on a Distribution-Sensitive Distance
  10. Altmetric Badge
    Chapter 9 Finding Association Rules with Some Very Frequent Attributes
  11. Altmetric Badge
    Chapter 10 Unsupervised Learning: Self-aggregation in Scaled Principal Component Space*
  12. Altmetric Badge
    Chapter 11 A Classification Approach for Prediction of Target Events in Temporal Sequences
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    Chapter 12 Privacy-Oriented Data Mining by Proof Checking
  14. Altmetric Badge
    Chapter 13 Choose Your Words Carefully: An Empirical Study of Feature Selection Metrics for Text Classification
  15. Altmetric Badge
    Chapter 14 Generating Actionable Knowledge by Expert-Guided Subgroup Discovery
  16. Altmetric Badge
    Chapter 15 Clustering Transactional Data
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    Chapter 16 Multiscale Comparison of Temporal Patterns in Time-Series Medical Databases
  18. Altmetric Badge
    Chapter 17 Association Rules for Expressing Gradual Dependencies
  19. Altmetric Badge
    Chapter 18 Support Approximations Using Bonferroni-Type Inequalities
  20. Altmetric Badge
    Chapter 19 Using Condensed Representations for Interactive Association Rule Mining
  21. Altmetric Badge
    Chapter 20 Predicting Rare Classes: Comparing Two-Phase Rule Induction to Cost-Sensitive Boosting
  22. Altmetric Badge
    Chapter 21 Dependency Detection in MobiMine and Random Matrices
  23. Altmetric Badge
    Chapter 22 Long-Term Learning for Web Search Engines
  24. Altmetric Badge
    Chapter 23 Spatial Subgroup Mining Integrated in an Object-Relational Spatial Database
  25. Altmetric Badge
    Chapter 24 Involving Aggregate Functions in Multi-relational Search
  26. Altmetric Badge
    Chapter 25 Information Extraction in Structured Documents Using Tree Automata Induction
  27. Altmetric Badge
    Chapter 26 Algebraic Techniques for Analysis of Large Discrete-Valued Datasets
  28. Altmetric Badge
    Chapter 27 Geography of Di.erences between Two Classes of Data
  29. Altmetric Badge
    Chapter 28 Rule Induction for Classification of Gene Expression Array Data
  30. Altmetric Badge
    Chapter 29 Clustering Ontology-Based Metadata in the Semantic Web
  31. Altmetric Badge
    Chapter 30 Iteratively Selecting Feature Subsets for Mining from High-Dimensional Databases
  32. Altmetric Badge
    Chapter 31 SVM Classification Using Sequences of Phonemes and Syllables
  33. Altmetric Badge
    Chapter 32 A Novel Web Text Mining Method Using the Discrete Cosine Transform
  34. Altmetric Badge
    Chapter 33 A Scalable Constant-Memory Sampling Algorithm for Pattern Discovery in Large Databases
  35. Altmetric Badge
    Chapter 34 Answering the Most Correlated N Association Rules Efficiently
  36. Altmetric Badge
    Chapter 35 Mining Hierarchical Decision Rules from Clinical Databases Using Rough Sets and Medical Diagnostic Model
  37. Altmetric Badge
    Chapter 36 Efficiently Mining Approximate Models of Associations in Evolving Databases
  38. Altmetric Badge
    Chapter 37 Explaining Predictions from a Neural Network Ensemble One at a Time
  39. Altmetric Badge
    Chapter 38 Structuring Domain-Specific Text Archives by Deriving a Probabilistic XML DTD
  40. Altmetric Badge
    Chapter 39 Separability Index in Supervised Learning
  41. Altmetric Badge
    Chapter 40 Finding Hidden Factors Using Independent Component Analysis
  42. Altmetric Badge
    Chapter 41 Reasoning with Classifiers*
  43. Altmetric Badge
    Chapter 42 A Kernel Approach for Learning from Almost Orthogonal Patterns
  44. Altmetric Badge
    Chapter 43 Learning with Mixture Models: Concepts and Applications
Attention for Chapter 11: A Classification Approach for Prediction of Target Events in Temporal Sequences
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

patent
3 patents

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
24 Mendeley
Summary Patents Dimensions citations
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
A Classification Approach for Prediction of Target Events in Temporal Sequences
Chapter number 11
Book title
Principles of Data Mining and Knowledge Discovery
Published in
Lecture notes in computer science, September 2002
DOI 10.1007/3-540-45681-3_11
Book ISBNs
978-3-54-044037-6, 978-3-54-045681-0
Authors

Carlotta Domeniconi, Chang-shing Perng, Ricardo Vilalta, Sheng Ma, Domeniconi, Carlotta, Perng, Chang-shing, Vilalta, Ricardo, Ma, Sheng

Editors

Tapio Elomaa, Heikki Mannila, Hannu Toivonen

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 33%
Student > Master 6 25%
Professor > Associate Professor 2 8%
Professor 2 8%
Student > Bachelor 2 8%
Other 2 8%
Unknown 2 8%
Readers by discipline Count As %
Computer Science 15 63%
Mathematics 1 4%
Business, Management and Accounting 1 4%
Economics, Econometrics and Finance 1 4%
Physics and Astronomy 1 4%
Other 2 8%
Unknown 3 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 24 May 2018.
All research outputs
#4,733,586
of 22,947,506 outputs
Outputs from Lecture notes in computer science
#1,572
of 8,129 outputs
Outputs of similar age
#7,715
of 46,545 outputs
Outputs of similar age from Lecture notes in computer science
#8
of 41 outputs
Altmetric has tracked 22,947,506 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,129 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done well, scoring higher than 79% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 46,545 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.

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