| Keynote Presentations |
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Incompleteness in Data Mining |
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1 | (1) |
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Hosagraphar Visvesvaraya Jagadish |
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Mining E-Commerce Data: The Good, the Bad, and the Ugly |
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2 | (1) |
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Seamless Integration of Data Mining with DBMS and Applications |
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3 | (1) |
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| Web Mining |
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Applying Pattern Mining to We Information Extraction |
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4 | (12) |
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Empirical Study of Recommender Systems Using Linear Classifiers |
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16 | (12) |
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iJADE eMiner---A Web-Based Mining Agent Based on Intelligent Java Agent Development Environment (iJADE) on Internet Shopping |
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28 | (13) |
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A Characterized Rating Recommend System |
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41 | (6) |
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Discovery of Frequent Tree Structured Patterns in Semistructured Web Documents |
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47 | (6) |
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| Text Mining |
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Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification |
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53 | (13) |
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Predictive Self-Organizing Networks for Text Categorization |
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66 | (12) |
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Meta-learning Models for Automatic Textual Document Categorization |
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78 | (12) |
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Efficient Algorithms for Concept Space Construction |
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90 | (12) |
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Topic Detection, Tracking, and Trend Analysis Using Self-Organizing Neural Networks |
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102 | (6) |
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Automatic Hypertext Construction Through a Text Mining Approach by Self-Organizing Maps |
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108 | (6) |
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| Applications and Tools |
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Semantic Expectation-Based Causation Knowledge Extraction: A Study on Hong Kong Stock Movement Analysis |
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114 | (10) |
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A Toolbox Approach to Flexible and Efficient Data Mining |
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124 | (12) |
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Determining Progression in Glaucoma Using Visual Fields |
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136 | (12) |
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Seabreeze Prediction Using Bayesian Networks |
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148 | (6) |
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Semi-supervised Learning in Medical Image Database |
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154 | (7) |
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On Application of Rough Data Mining Methods to Automatic Construction of Student Models |
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161 | (6) |
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| Concept Hierarchies |
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Concept Approximation in Concept Lattice |
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167 | (7) |
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Generating Concept Hierarchies/Networks: Mining Additional Semantics in Relational Data |
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174 | (12) |
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Representing Large Concept Hierarchies Using Lattice Data Structure |
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186 | (12) |
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| Feature Selection |
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Feature Selection for Temporal Health Records |
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198 | (12) |
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Boosting the Performance of Nearest Neighbour Methods with Feature Selection |
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210 | (12) |
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Feature Selection for Meta-learning |
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222 | (12) |
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| Interestingness |
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Efficient mining of Niches and Set Routines |
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234 | (13) |
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Evaluation of Interestingness Measures for Ranking Discovered Knowledge |
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247 | (13) |
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Peculiarity Oriented Mining and Its Application for Knowledge Discovery in Amino-Acid Data |
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260 | (10) |
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| Sequence Mining |
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Mining Sequence Patterns from Wind Tunnel Experimental Data for Flight Control |
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270 | (12) |
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Scalable Hierarchical Clustering Method for Sequences of Categorical Values |
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282 | (12) |
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FFS---An I/O-Efficient Algorithm for Mining Frequent Sequences |
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294 | (12) |
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Sequential Index Structure for Content-Based Retrieval |
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306 | (6) |
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| Spatial and Temporal Mining |
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The S2 Tree: An Index Structure for Subsequence Matching of Spatial Objects |
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312 | (12) |
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Temporal Data Mining Using Hidden Markov-Local Polynomial Models |
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324 | (12) |
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Patterns Discovery Based on Time-Series Decomposition |
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336 | (12) |
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Criteria on Proximity Graphs for Boundary Extraction and Spatial Clustering |
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348 | (10) |
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Micro Similarity Queries in Time Series Database |
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358 | (6) |
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| Association Mining |
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Mining Optimal Class Association rule Set |
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364 | (12) |
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Generating Frequent Patterns with the Frequent Pattern List |
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376 | (11) |
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User-Defined Association Mining |
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387 | (13) |
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Direct and Incremental Computing of Maximal Covering Rules |
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400 | (6) |
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Towards Efficient Data Re-mining (DRM) |
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406 | (7) |
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Data Allocation Algorithm for Parallel Association Rule Discovery |
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413 | (8) |
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| Classification and Rule Induction |
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Direct Domain Knowledge Inclusion in the PA3 Rule Induction Algorithm |
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421 | (12) |
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Hierarchical Classification of Documents with Error Control |
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433 | (11) |
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An Efficient Data Compression Approach to the Classification Task |
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444 | (11) |
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Combining the Strength of Pattern Frequency and Distance for Classification |
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455 | (12) |
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A Scalable Algorithm for Rule Post-pruning of Large Decision Trees |
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467 | (10) |
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Optimizing the Induction of Alternating Decision Trees |
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477 | (11) |
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Building Behaviour Knowledge Space to Make Classification Decision |
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488 | (7) |
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| Clustering |
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Efficient Hierarchical Clustering Algorithms Using Partially Overlapping Partitions |
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495 | (12) |
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A Rough Set-Based Clustering Method with Modification of Equivalence Relations |
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507 | (6) |
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Importance of Individual Variables in the k-Means Algorithm |
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513 | (6) |
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A Hybrid Approach to Clustering in Very Large Databases |
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519 | (6) |
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| Advanced Topics and New Methods |
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A Similarity Indexing Method for the Data Warehousing---Bit-Wise Indexing Method |
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525 | (13) |
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Rule Reduction over Numerical Attributes in Decision Trees Using Multilayer Perceptron |
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538 | (12) |
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Knowledge Acquisition from Both Human Expert and Data |
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550 | (12) |
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Neighborhood Dependencies for Prediction |
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562 | (6) |
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Learning Bayesian Networks with Hidden Variables Using the Combination of EM and Evolutionary Algorithms |
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568 | (7) |
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Interactive Construction of Decision Trees |
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575 | (6) |
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An Improved Learning Algorithm for Augmented Naive Bayes |
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581 | (6) |
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Generalised RBE Networks Trained Using an IBL Algorithm for Mining Symbolic Data |
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587 | (8) |
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| Author Index |
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Biežāk uzdotie jautājumi par e-grāmatām