Third IEEE International Conference on Data Mining: ICDM 2003


Papers from a November 2003 conference cover topics related to data mining theory, systems, and applications, including data mining and machine learning algorithms and methods in traditional and new areas, mining text and semi-structured data, data and knowledge representation for data mining, post-processing of data mining results, and integration of data warehousing, OLAP, and data mining. Other topics are quality assessment, pattern recognition and scientific discovery, security and privacy, and the social ...
See more details below
This Paperback is Not Available through
Sending request ...


Papers from a November 2003 conference cover topics related to data mining theory, systems, and applications, including data mining and machine learning algorithms and methods in traditional and new areas, mining text and semi-structured data, data and knowledge representation for data mining, post-processing of data mining results, and integration of data warehousing, OLAP, and data mining. Other topics are quality assessment, pattern recognition and scientific discovery, security and privacy, and the social impact of data mining. Material on soft computing examines developments in neural networks, fuzzy logic, evolutionary computation, and rough sets. There is no subject index. Annotation ©2004 Book News, Inc., Portland, OR
Read More Show Less

Product Details

  • ISBN-13: 9780769519784
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 1/28/2003
  • Pages: 782

Table of Contents

Welcome to ICDM 2003
Conference organization
Steering committee
Program committee
External reviewers
Corporate sponsors
Invited talks
Efficient multidimensional quantitative hypotheses generation 3
ExAMminder : optimized level-wise frequent pattern mining with monotone contraints 11
Mining high utility itemsets 19
Zigzag : a new algorithm for mining large inclusion dependencies in databases 27
Frequent sub-structure-based approaches for classifying chemical compounds 35
Optimized disjunctive association rules via sampling 43
Is random model better? on its accuracy and efficiency 51
Identifying markov blankets with decision tree induction 59
Reliable detection of episodes in event sequences 67
A dynamic adaptive self-organising hybrid model for text clustering 75
Mining significant pairs of patterns from graph structures with class labels 83
Scalable model-based clustering by working on data summaries 91
On the privacy preserving properties of random data perturbation techniques 99
Semantic log analysis based on a user query behavior model 107
Clustering of time series subsequences is meaningless : implications for previous and future research 115
Dynamic weighted majority : a new ensemble method for tracking concept drift 123
Probabilistic noise identification and data cleaning 131
Localized prediction of continuous target variables using hierarchical clustering 139
An algebra for inductive query evaluation 147
Direct interesting rule generation 155
Spatial interest pixels (SIPs) : useful low-level features of visual media data 163
Unsupervised link discovery in multi-relational data via rarity analysis 171
Building text classifiers using positive and unlabeled examples 179
OP-cluster : clustering by tendency in high dimensional space 187
Parsing without a grammar : making sense of unknown file formats 195
Probabilistic user behavior models 203
Privacy-preserving distributed clustering using generative models 211
Change profiles 219
Complex spatial relationships 227
TECNO-STREAMS : tracking evolving clusters in noisy data streams with a scalable immune system learning model 235
Efficient nonlinear dimension reduction for clustered data using kernel functions 243
Sequence modeling with mixtures of conditional maximum entropy distributions 251
MaPle : a fast algorithm for maximal pattern-based clustering 259
Exploiting unlabeled data for improving accuracy of predictive data mining 267
Statistical relational learning for document mining 275
Integrating customer value considerations into predictive modeling 283
A high-performance distributed algorithm for mining association rules 291
Introducing uncertainty into pattern discovery in temporal event sequences 299
Evolutionary Gabor filter optimization with application to vehicle detection 307
Detecting interesting exceptions from medical test data with visual summarization 315
Learning Bayesian networks from incomplete data based on EMI method 323
Combining multiple weak clusterings 331
Visualization of rule's similarity using multidimensional scaling 339
TSP : Mining Top-K closed sequential patterns 347
Interactive visualization and navigation in large data collections using the hyperbolic space 355
Association rule mining in peer-to-peer systems 363
MPIS : maximal-profit item selection with cross-selling considerations 371
Efficient data mining for maximal frequent subtrees 379
Mining strong affinity association patterns in data sets with skewed support distribution 387
On precision and recall of multi-attribute data extraction from semistructured sources 395
Mining plans for customer-class transformation 403
Segmenting customer transactions using a pattern-based clustering approach 411
A new optimization criterion for generalized discriminant analysis on undersampled problems 419
Sentiment analyzer : extracting sentiments about a given topic using natural language processing techniques 427
Cost-sensitive learning by cost-proportionate example weighting 435
CBC : clustering based text classification requiring minimal labeled data 443
Regression clustering 451
Model-based clustering with soft balancing 459
Integrating fuzziness into OLAP for multidimensional fuzzy association rules mining 469
Analyzing high-dimensional data by subspace validity 473
Objective and subjective algorithms for grouping association rules 477
Efficient subsequence matching in time series databases under time and amplitude transformations 481
A fast algorithm for computing hypergraph transversals and its application in mining emerging patterns 485
Mining relevant text from unlabelled documents 489
A user-driven and quality-oriented visualization for mining association rules 493
Towards simple, easy-to-understand, yet accurate classifiers 497
Validating and refining clusters via visual rendering 501
Icon-based visualization of large high-dimensional datasets 505
Indexing and mining free trees 509
T-trees, vertical partitioning and distributed association rule mining 513
Information theoretic clustering of sparse co-occurrence data 517
Links between Kleinberg's hubs and authorities, correspondence analysis, and Markov chains 521
Fast PNN-based clustering using K-nearest neighbor graph 525
The rough set approach to association rule mining 529
Comparing pure parallel ensemble creation techniques against bagging 533
Improving home automation by discovering regularly occurring device usage patterns 537
Ontologies improve text document clustering 541
The hybrid poisson aspect model for personalized shopping recommendation 545
Efficient mining of frequent subgraphs in the presence of isomorphism 549
Comparing naive bayes, decision trees, and SVM with AUC and accuracy 553
SVM based models for predicting foreign currency exchange rates 557
Facilitating fuzzy association rules mining by using multi-objective genetic algorithms for automated clustering 561
PixelMaps : a new visual data mining approach for analyzing large spatial data sets 565
Effectiveness of information extraction, multi-relational, and semi-supervised learning for predicting functional properties of genes 569
Tractable group detection on large link data sets 573
Tree-structured partitioning based on splitting histograms of distances 577
CoMine : efficient mining of correlated patterns 581
Ensembles of cascading trees 585
Using discriminant analysis for multi-class classification 589
Interpretations of association rules by granular computing 593
Algorithms for spatial outlier detection 597
Learning rules for anomaly detection of hostile network traffic 601
An algorithm for the exact computation of the centroid of higher dimensional polyhedra and its application to kernel machines 605
Simple estimators for relational Bayesian classifiers 609
Protecting sensitive knowledge by data sanitization 613
Mining frequent itemsets in distributed and dynamic databases 617
Structure search and stability enhancement of bayesian networks 621
Privacy-preserving collaborative filtering using randomized perturbation techniques 625
Semantic role parsing : adding semantic structure to unstructured text 629
Mining semantic networks for knowledge discovery 633
Impact studies and sensitivity analysis in medical data mining with roc-based genetic learning 637
K-D decision tree : an accelerated and memory efficient nearest neighbor classifier 641
Mining the web to discover the meanings of an ambiguous word 645
A hybrid data-mining approach in genomics and text structures 649
Model stability : a key factor in determining whether an algorithm produces an optimal model from a matching distribution 653
Enhancing techniques for efficient topic hierarchy integration 657
Pattern discovery based on rule induction and taxonomy generation 661
Active sampling for feature selection 665
Combining the web content and usage mining to understand the visitor behavior in a web site 669
Class decomposition via clustering : a new framework for low-variance classifiers 673
Bootstrapping rule induction 677
Center-based indexing for nearest neighbors search 681
Postprocessing decision trees to extract actionable knowledge 685
Frequent-pattern based iterative projected clustering 689
General MC : estimating boundary of positive class from small positive data 693
Clustering item data sets with association-taxonomy similarity 697
Dimensionality reduction using kernel pooled local discriminant information 701
A feature selection framework for text filtering 705
A K-NN associated fuzzy evidential reasoning classifier with adaptive neighbor selection 709
Findings from a practical project concerning web usage mining 715
Read More Show Less

Customer Reviews

Be the first to write a review
( 0 )
Rating Distribution

5 Star


4 Star


3 Star


2 Star


1 Star


Your Rating:

Your Name: Create a Pen Name or

Barnes & Review Rules

Our reader reviews allow you to share your comments on titles you liked, or didn't, with others. By submitting an online review, you are representing to Barnes & that all information contained in your review is original and accurate in all respects, and that the submission of such content by you and the posting of such content by Barnes & does not and will not violate the rights of any third party. Please follow the rules below to help ensure that your review can be posted.

Reviews by Our Customers Under the Age of 13

We highly value and respect everyone's opinion concerning the titles we offer. However, we cannot allow persons under the age of 13 to have accounts at or to post customer reviews. Please see our Terms of Use for more details.

What to exclude from your review:

Please do not write about reviews, commentary, or information posted on the product page. If you see any errors in the information on the product page, please send us an email.

Reviews should not contain any of the following:

  • - HTML tags, profanity, obscenities, vulgarities, or comments that defame anyone
  • - Time-sensitive information such as tour dates, signings, lectures, etc.
  • - Single-word reviews. Other people will read your review to discover why you liked or didn't like the title. Be descriptive.
  • - Comments focusing on the author or that may ruin the ending for others
  • - Phone numbers, addresses, URLs
  • - Pricing and availability information or alternative ordering information
  • - Advertisements or commercial solicitation


  • - By submitting a review, you grant to Barnes & and its sublicensees the royalty-free, perpetual, irrevocable right and license to use the review in accordance with the Barnes & Terms of Use.
  • - Barnes & reserves the right not to post any review -- particularly those that do not follow the terms and conditions of these Rules. Barnes & also reserves the right to remove any review at any time without notice.
  • - See Terms of Use for other conditions and disclaimers.
Search for Products You'd Like to Recommend

Recommend other products that relate to your review. Just search for them below and share!

Create a Pen Name

Your Pen Name is your unique identity on It will appear on the reviews you write and other website activities. Your Pen Name cannot be edited, changed or deleted once submitted.

Your Pen Name can be any combination of alphanumeric characters (plus - and _), and must be at least two characters long.

Continue Anonymously

    If you find inappropriate content, please report it to Barnes & Noble
    Why is this product inappropriate?
    Comments (optional)