| Protection or privacy? : data mining and personal data | p. 1 |
| The changing face of Web search | p. 11 |
| Data mining for surveillance applications | p. 12 |
| A multiclass classification method based on output design | p. 15 |
| Regularized semi-supervised classification on manifold | p. 20 |
| Similarity-based sparse feature extraction using local manifold learning | p. 30 |
| Generalized conditional entropy and a metric splitting criterion for decision trees | p. 35 |
| RNBL-MN : a recursive naive Bayes learner for sequence classification | p. 45 |
| TRIPPER : rule learning using taxonomies | p. 55 |
| Using weighted nearest neighbor to benefit from unlabeled data | p. 60 |
| Constructive meta-level feature selection method based on method repositories | p. 70 |
| Variable randomness in decision tree ensembles | p. 81 |
| Further improving emerging pattern based classifiers via bagging | p. 91 |
| Improving on bagging with input smearing | p. 97 |
| Boosting prediction accuracy on imbalanced datasets with SVM ensembles | p. 107 |
| DeLiClu : boosting robustness, completeness, usability, and efficiency of hierarchical clustering by a closest pair ranking | p. 119 |
| Iterative clustering analysis for grouping missing data in gene expression profiles | p. 129 |
| An EM-approach for clustering multi-instance objects | p. 139 |
| Mining maximal correlated member clusters in high dimensional database | p. 149 |
| Hierarchical clustering based on mathematical optimization | p. 160 |
| Clustering multi-represented objects using combination trees | p. 174 |
| Parallel density-based clustering of complex objects | p. 179 |
| Neighborhood density method for selecting initial cluster centers in K-means clustering | p. 189 |
| Uncertain data mining : an example in clustering location data | p. 199 |
| Parallel randomized support vector machine | p. 205 |
| [epsilon]-tube based pattern selection for support vector machines | p. 215 |
| Self-adaptive two-phase support vector clustering for multi-relational data mining | p. 225 |
| One-class support vector machines for recommendation tasks | p. 230 |
| Heterogeneous information integration in hierarchical text classification | p. 240 |
| FISA : feature-based instance selection for imbalanced text classification | p. 250 |
| Dynamic category profiling for text filtering and classification | p. 255 |
| Detecting citation types using finite-state machines | p. 265 |
| A systematic study of parameter correlations in large scale duplicate document detection | p. 275 |
| Comparison of documents classification techniques to classify medical reports | p. 285 |
| XCLS : a fast and effective clustering algorithm for heterogenous XML documents | p. 292 |
| Clustering large collection of biomedical literature based on ontology-enriched bipartite graph representation and mutual refinement strategy | p. 303 |
| Level-biased statistics in the hierarchical structure of the Web | p. 313 |
| Cleopatra : evolutionary pattern-based clustering of Web usage data | p. 323 |
| Extracting and summarizing hot item features across different auction Web sites | p. 334 |
| Clustering Web sessions by levels of page similarity | p. 346 |
| iWed : an integrated multigraph cut-based approach for detecting events from a Website | p. 351 |
| Enhancing duplicate collection detection through replica boundary discovery | p. 361 |
| Summarization and visualization of communication patterns in a large-scale social network | p. 371 |
| Patterns of influence in a recommendation network | p. 380 |
| Constructing decision trees for graph-structured data by chunkingless graph-based induction | p. 390 |
| Combining smooth graphs with semi-supervised classification | p. 400 |
| Network data mining : discovering patterns of interaction between attributes | p. 410 |
| SGPM : static group pattern mining using apriori-like sliding window | p. 415 |
| Mining temporal indirect associations | p. 425 |
| Mining top-K frequent closed itemsets is not in APX | p. 435 |
| Quality-aware association rule mining | p. 440 |
| IMB3-miner : mining induced/embedded subtrees by constraining the level of embedding | p. 450 |
| Maintaining frequent itemsets over high-speed data streams | p. 462 |
| Generalized disjunction-free representation of frequents patterns with at most k negations | p. 468 |
| Mining interesting imperfectly sporadic rules | p. 473 |
| Improved negative-border online mining approaches | p. 483 |
| Association-based dissimilarity measures for categorical data : limitation and improvement | p. 493 |
| Is frequency enough for decision makers to make decisions? | p. 499 |
| Ramp : high performance frequent itemset mining with efficient bit-vector projection technique | p. 504 |
| Evaluating a rule evaluation support method based on objective rule evaluation indices | p. 509 |
| Scoring method for tumor prediction from microarray data using an evolutionary fuzzy classifier | p. 520 |
| Efficient discovery of structural motifs from protein sequences with combination of flexible intra- and inter-block gap constraints | p. 530 |
| Finding consensus patterns in very scarce biosequence samples from their minimal multiple generalizations | p. 540 |
| Kernels on lists and sets over relational algebra : an application to classification of protein fingerprints | p. 546 |
| Mining quantitative maximal hyperclique patterns : a summary of results | p. 552 |
| A nonparametric outlier detection for effectively discovering top-N outliers from engineering data | p. 557 |
| A fast greedy algorithm for outlier mining | p. 567 |
| Ranking outliers using symmetric neighborhood relationship | p. 577 |
| Construction of finite automata for intrusion detection from system call sequences by genetic algorithms | p. 594 |
| An adaptive intrusion detection algorithm based on clustering and Kernel-method | p. 603 |
| Weighted intra-transactional rule mining for database intrusion detection | p. 611 |
| On robust and effective K-anonymity in large databases | p. 621 |
| Achieving private recommendations using randomized response techniques | p. 637 |
| Privacy-preserving svm classification on vertically partitioned data | p. 647 |
| Data mining using relational database management systems | p. 657 |
| Bias-free hypothesis evaluation in multirelational domains | p. 668 |
| Enhanced DB-subdue : supporting subtle aspects of graph mining using a relational approach | p. 673 |
| Multimedia semantics integration using linguistic model | p. 679 |
| A novel indexing approach for efficient and fast similarity search of captured motions | p. 689 |
| Mining frequent spatial patterns in image databases | p. 699 |
| Image classification via LZ78 based string kernel : a comparative study | p. 704 |
| Distributed pattern discovery in multiple streams | p. 713 |
| COMET : event-driven clustering over multiple evolving streams | p. 719 |
| Variable support mining of frequent itemsets over data streams using synopsis vectors | p. 724 |
| Hardware enhanced mining for association rules | p. 729 |
| A single index approach for time-series subsequence matching that supports moving average transform of arbitrary order | p. 739 |
| Efficient mining of emerging events in a dynamic spatiotemporal environment | p. 750 |
| A multi-hierarchical representation for similarity measurement of time series | p. 755 |
| Multistep-ahead time series prediction | p. 765 |
| Sequential pattern mining with time intervals | p. 775 |
| A wavelet analysis based data processing for time series of data mining predicting | p. 780 |
| Intelligent particle swarm optimization in multi-objective problems | p. 790 |
| Hidden space principal component analysis | p. 801 |
| Neighbor line-based locally linear embedding | p. 806 |
| Predicting rare extreme values | p. 816 |
| Domain-driven actionable knowledge discovery in the real world | p. 821 |
| Evaluation of attribute-aware recommender system algorithms on data with varying characteristics | p. 831 |
| An intelligent system based on kernel methods for crop yield prediction | p. 841 |
| A machine learning application for human resource data mining problem | p. 847 |
| Towards automated design of large-scale circuits by combining evolutionary design with data mining | p. 857 |
| Mining unexpected associations for signalling potential adverse drug reactions from administrative health databases | p. 867 |
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