Advances in knowledge discovery and data mining : 7th Pacific-Asia Conference, PAKDD 2003, Seoul, Korea, April 30 May 2, 2003 : proceedings
The 7th Paci?c Asia Conference on Knowledge Discovery and Data Mining (PAKDD) was held from April 30 to May 2, 2003 in the Convention and Ex- bition Center (COEX), Seoul, Korea. The PAKDD conference is a major forum for academic researchers and industry practitioners in the Paci?c Asia region to sha...
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| Coauteur: | |
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| Andere auteurs: | , , |
| Formaat: | Livre numérique |
| Taal: | Anglais |
| Gepubliceerd in: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Reeks: | Lecture notes in computer science. Lecture notes in artificial intelligence
2637 |
| Onderwerpen: | |
| Online toegang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Opmerking: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Advances in knowledge discovery and data mining, 7th Pacific-Asia Conference, PAKDD 2003, Seoul. Korea, April 30-May 2, 2003, proceedings, Kyu-Young Whang, Jongwoo Jeon, Kyuseok Shim, ... [et al.] (eds.), Berlin, Springer, 2003, 1 vol. (XVIII-610 p.), Lecture notes in computer science, 3-540-04760-3 • Advances in Knowledge Discovery and Data Mining, Texte imprimé, 9783662174227 |
Inhoudsopgave:
- Industrial Papers (Invited)
- Data Mining as an Automated Service
- Trends and Challenges in the Industrial Applications of KDD
- Stream Mining I
- Finding Event-Oriented Patterns in Long Temporal Sequences
- Mining Frequent Episodes for Relating Financial Events and Stock Trends
- Graph Mining
- An Efficient Algorithm of Frequent Connected Subgraph Extraction
- Classifier Construction by Graph-Based Induction for Graph-Structured Data
- Clustering I
- Comparison of the Performance of Center-Based Clustering Algorithms
- Automatic Extraction of Clusters from Hierarchical Clustering Representations
- Text Mining
- Large Scale Unstructured Document Classification Using Unlabeled Data and Syntactic Information
- Extracting Shared Topics of Multiple Documents
- An Empirical Study on Dimensionality Optimization in Text Mining for Linguistic Knowledge Acquisition
- A Semi-supervised Algorithm for Pattern Discovery in Information Extraction from Textual Data
- Bio Mining
- Mining Patterns of Dyspepsia Symptoms Across Time Points Using Constraint Association Rules
- Predicting Protein Structural Class from Closed Protein Sequences
- Learning Rules to Extract Protein Interactions from Biomedical Text
- Predicting Protein Interactions in Human by Homologous Interactions in Yeast
- Web Mining
- Mining the Customer s Up-To-Moment Preferences for E-commerce Recommendation
- A Graph-Based Optimization Algorithm for Website Topology Using Interesting Association Rules
- A Markovian Approach for Web User Profiling and Clustering
- Extracting User Interests from Bookmarks on the Web
- Stream Mining II
- Mining Frequent Instances on Workflows
- Real Time Video Data Mining for Surveillance Video Streams
- Distinguishing Causal and Acausal Temporal Relations
- Bayesian Networks
- OnlineBayes Point Machines
- Exploiting Hierarchical Domain Values for Bayesian Learning
- A New Restricted Bayesian Network Classifier
- Clustering II
- AGRID: An Efficient Algorithm for Clustering Large High-Dimensional Datasets
- Multi-level Clustering and Reasoning about Its Clusters Using Region Connection Calculus
- An Efficient Cell-Based Clustering Method for Handling Large, High-Dimensional Data
- Association Rules I
- Enhancing SWF for Incremental Association Mining by Itemset Maintenance
- Reducing Rule Covers with Deterministic Error Bounds
- Evolutionary Approach for Mining Association Rules on Dynamic Databases
- Semi-structured Data Mining
- Position Coded Pre-order Linked WAP-Tree for Web Log Sequential Pattern Mining
- An Integrated System of Mining HTML Texts and Filtering Structured Documents
- A New Sequential Mining Approach to XML Document Similarity Computation
- Classification I
- Optimization of Fuzzy Rules for Classification Using Genetic Algorithm
- Fast Pattern Selection for Support Vector Classifiers
- Averaged Boosting: A Noise-Robust Ensemble Method
- Improving Performance of Decision Tree Algorithms with Multi-edited Nearest Neighbor Rule
- Data Analysis
- HOT: Hypergraph-Based Outlier Test for Categorical Data
- A Method for Aggregating Partitions, Applications in K.D.D.
- Efficiently Computing Iceberg Cubes with Complex Constraints through Bounding
- Extraction of Tag Tree Patterns with Contractible Variables from Irregular Semistructured Data
- Association Rules II
- Step-by-Step Regression: A More Efficient Alternative for Polynomial Multiple Linear Regression in Stream Cube
- Progressive Weighted Miner: An Efficient Method for Time-Constraint Mining
- Mining Open Source Software (OSS) Data Using Association Rules Network
- Parallel FP-Growth on PC Cluster
- Feature Selection
- Active Feature Selection Using Classes
- Electricity Based External Similarity of Categorical Attributes
- Weighted Proportional k-Interval Discretization for Naive-Bayes Classifiers
- Dealing with Relative Similarity in Clustering: An Indiscernibility Based Approach
- Stream Mining III
- Considering Correlation between Variables to Improve Spatiotemporal Forecasting
- Correlation Analysis of Spatial Time Series Datasets: A Filter-and-Refine Approach
- When to Update the Sequential Patterns of Stream Data?
- Clustering III
- A New Clustering Algorithm for Transaction Data via Caucus
- DBRS: A Density-Based Spatial Clustering Method with Random Sampling
- Optimized Clustering for Anomaly Intrusion Detection
- Classification II
- Finding Frequent Subgraphs from Graph Structured Data with Geometric Information and Its Application to Lossless Compression
- Upgrading ILP Rules to First-Order Bayesian Networks
- A Clustering Validity Assessment Index.