SIGKDD(KDD) 2001 论文列表Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, San Francisco, CA, USA, August 26-29, 2001. |
Mining web logs for prediction models in WWW caching and prefetching.
Mining user session data to facilitate user interaction with a customer service knowledge base in RightNow Web.
Knowledge base maintenance using knowledge gap analysis.
Evaluation of prediction models for marketing campaigns.
Funnel report mining for the MSN network.
Mining from open answers in questionnaire data.
Data mining techniques to improve forecast accuracy in airline business.
REVI-MINER, a KDD-environment for deviation detection and analysis of warranty and goodwill cost statements in automotive industry.
Magical thinking in data mining: lessons from CoIL challenge 2000.
Estimating business targets.
Interactive path analysis of web site traffic.
Segmentation-based modeling for advanced targeted marketing.
Chidanand Apté Eric Bibelnieks Ramesh Natarajan Edwin P. D. Pednault Fateh Tipu Deb Campbell Bryan Nelson
Real world performance of association rule algorithms.
Infominer: mining surprising periodic patterns.
Discovering outlier filtering rules from unlabeled data: combining a supervised learner with an unsupervised learner.
Discovering associations with numeric variables.
A streaming ensemble algorithm (SEA) for large-scale classification.
Detecting graph-based spatial outliers: algorithms and applications (a summary of results).
TreeDT: gene mapping by tree disequilibrium test.
Experimental comparisons of online and batch versions of bagging and boosting.
Mining frequent neighboring class sets in spatial databases.
Data filtering for automatic classification of rocks from reflectance spectra.
Finding simple intensity descriptions from event sequence data.
Discovering the set of fundamental rule changes.
Identifying non-actionable association rules.
DIRT @SBT@discovery of inference rules from text.
Induction of semantic classes from natural language text.
The distributed boosting algorithm.
Mining a stream of transactions for customer patterns.
Generalized clustering, supervised learning, and data assignment.
Mining top-n local outliers in large databases.
Solving regression problems with rule-based ensemble classifiers.
Clustering spatial data using random walks.
A spectral method to separate disconnected and nearly-disconnected web graph components.
Co-clustering documents and words using bipartite spectral graph partitioning.
A robust and scalable clustering algorithm for mixed type attributes in large database environment.
PVA: a self-adaptive personal view agent system.
Gaining insights into support vector machine pattern classifiers using projection-based tour methods.
Random projection in dimensionality reduction: applications to image and text data.
Fast ordering of large categorical datasets for better visualization.
Evaluating the novelty of text-mined rules using lexical knowledge.
Mining massively incomplete data sets by conceptual reconstruction.
A human-computer cooperative system for effective high dimensional clustering.
Data mining case study: modeling the behavior of offenders who commit serious sexual assaults.
Learning and making decisions when costs and probabilities are both unknown.
Efficient discovery of error-tolerant frequent itemsets in high dimensions.
Tri-plots: scalable tools for multidimensional data mining.
Extracting collective probabilistic forecasts from web games.
Probabilistic query models for transaction data.
Personalization from incomplete data: what you don't know can hurt.
Discovering unexpected information from your competitors' web sites.
Molecular feature mining in HIV data.
Robust space transformations for distance-based operations.
Ensemble-index: a new approach to indexing large databases.
Visualizing multi-dimensional clusters, trends, and outliers using star coordinates.
Mining time-changing data streams.
Data mining with sparse grids using simplicial basis functions.
Proximal support vector machine classifiers.
Empirical bayes screening for multi-item associations.
Mining the network value of customers.
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces.
Probabilistic modeling of transaction data with applications to profiling, visualization, and prediction.
Data mining criteria for tree-based regression and classification.
The "DGX" distribution for mining massive, skewed data.
Recommender systems in commerce and community.
Data mining platform for database developers.
Mining e-commerce data: the good, the bad, and the ugly.
Data mining: are we there yet?
Applications of generalized support vector machines to predictive modeling.
Mass collaboration and data mining.
Extracting targeted data from the web.
Challenges for knowledge discovery in biology.