SIGKDD(KDD) 2004 论文列表
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Seattle, Washington, USA, August 22-25, 2004.
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Analytical view of business data.
1-dimensional splines as building blocks for improving accuracy of risk outcomes models.
Learning a complex metabolomic dataset using random forests and support vector machines.
Document preprocessing for naive Bayes classification and clustering with mixture of multinomials.
Programming the K-means clustering algorithm in SQL.
Mining traffic data from probe-car system for travel time prediction.
Tracking dynamics of topic trends using a finite mixture model.
A system for automated mapping of bill-of-materials part numbers.
ANN quality diagnostic models for packaging manufacturing: an industrial data mining case study.
A general approach to incorporate data quality matrices into data mining algorithms.
Feature selection in scientific applications.
Exploring the community structure of newsgroups.
Interactive training of advanced classifiers for mining remote sensing image archives.
Cross channel optimized marketing by reinforcement learning.
Optimal randomization for privacy preserving data mining.
A DEA approach for model combination.
A data mining approach to modeling relationships among categories in image collection.
A cross-collection mixture model for comparative text mining.
Redundancy based feature selection for microarray data.
2PXMiner: an efficient two pass mining of frequent XML query patterns.
IMMC: incremental maximum margin criterion.
Mining scale-free networks using geodesic clustering.
Privacy-preserving Bayesian network structure computation on distributed heterogeneous data.
Rotation invariant distance measures for trajectories.
A generative probabilistic approach to visualizing sets of symbolic sequences.
Ordering patterns by combining opinions from multiple sources.
Generalizing the notion of support.
Dense itemsets.
Privacy preserving regression modelling via distributed computation.
Identifying early buyers from purchase data.
Cluster-based concept invention for statistical relational learning.
Estimating the size of the telephone universe: a Bayesian Mark-recapture approach.
Automatic multimedia cross-modal correlation discovery.
A quickstart in frequent structure mining can make a difference.
Semantic representation: search and mining of multimedia content.
Sleeved coclustering.
The IOC algorithm: efficient many-class non-parametric classification for high-dimensional data.
A framework for ontology-driven subspace clustering.
Clustering moving objects.
Learning spatially variant dissimilarity (SVaD) measures.
Improved robustness of signature-based near-replica detection via lexicon randomization.
When do data mining results violate privacy?
Why collective inference improves relational classification.
On detecting space-time clusters.
SPIN: mining maximal frequent subgraphs from graph databases.
Discovering additive structure in black box functions.
Diagnosing extrapolation: tree-based density estimation.
k-TTP: a new privacy model for large-scale distributed environments.
A microeconomic data mining problem: customer-oriented catalog segmentation.
Kernel k-means: spectral clustering and normalized cuts.
Locating secret messages in images.
Belief state approaches to signaling alarms in surveillance systems.
Parallel computation of high dimensional robust correlation and covariance matrices.
IncSpan: incremental mining of sequential patterns in large database.
Column-generation boosting methods for mixture of kernels.
An objective evaluation criterion for clustering.
A generalized maximum entropy approach to bregman co-clustering and matrix approximation.
On demand classification of data streams.
V-Miner: using enhanced parallel coordinates to mine product design and test data.
Density-based spam detector.
Predicting prostate cancer recurrence via maximizing the concordance index.
Learning to detect malicious executables in the wild.
Visually mining and monitoring massive time series.
Effective localized regression for damage detection in large complex mechanical structures.
Eigenspace-based anomaly detection in computer systems.
Mining coherent gene clusters from gene-sample-time microarray data.
Early detection of insider trading in option markets.
A rank sum test method for informative gene discovery.
Predicting customer shopping lists from point-of-sale purchase data.
TiVo: making show recommendations using a distributed collaborative filtering architecture.
Fast mining of spatial collocations.
On the discovery of significant statistical quantitative rules.
IDR/QR: an incremental dimension reduction algorithm via QR decomposition.
GPCA: an efficient dimension reduction scheme for image compression and retrieval.
The complexity of mining maximal frequent itemsets and maximal frequent patterns.
Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pairs.
Incorporating prior knowledge with weighted margin support vector machines.
Scalable mining of large disk-based graph databases.
Probabilistic author-topic models for information discovery.
Support envelopes: a technique for exploring the structure of association patterns.
A Bayesian network framework for reject inference.
Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage.
Turning CARTwheels: an alternating algorithm for mining redescriptions.
Rapid detection of significant spatial clusters.
Machine learning for online query relaxation.
Mining, indexing, and querying historical spatiotemporal data.
Incremental maintenance of quotient cube for median.
A graph-theoretic approach to extract storylines from search results.
Towards parameter-free data mining.
Web usage mining based on probabilistic latent semantic analysis.
Mining the space of graph properties.
Interestingness of frequent itemsets using Bayesian networks as background knowledge.
Mining and summarizing customer reviews.
Cyclic pattern kernels for predictive graph mining.
Discovering complex matchings across web query interfaces: a correlation mining approach.
Efficient closed pattern mining in the presence of tough block constraints.
Systematic data selection to mine concept-drifting data streams.
Fast discovery of connection subgraphs.
Regularized multi--task learning.
Adversarial classification.
Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods.
Fully automatic cross-associations.
Data mining in metric space: an empirical analysis of supervised learning performance criteria.
A probabilistic framework for semi-supervised clustering.
Clustering time series from ARMA models with clipped data.
Fast nonlinear regression via eigenimages applied to galactic morphology.
Recovering latent time-series from their observed sums: network tomography with particle filters.
Mining reference tables for automatic text segmentation.
Approximating a collection of frequent sets.
An iterative method for multi-class cost-sensitive learning.
Graphical models for data mining.
User-centered design for KDD.
