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1st ICDM 2001: San Jose, California, USA
- Nick Cercone, Tsau Young Lin, Xindong Wu:
Proceedings of the 2001 IEEE International Conference on Data Mining, 29 November - 2 December 2001, San Jose, California, USA. IEEE Computer Society 2001, ISBN 0-7695-1119-8
Regular Papers
- Charu C. Aggarwal, Philip S. Yu:
On Effective Conceptual Indexing and Similarity Search in Text Data. 3-10 - Aijun An, Yuanyuan Wang:
Comparisons of Classification Methods for Screening Potential Compounds. 11-18 - Michael Anderson:
Knowledge Discovery from Diagrammatically Represented Data. 19-26 - Suhail Ansari, Ron Kohavi, Llew Mason, Zijian Zheng:
Integrating E-Commerce and Data Mining: Architecture and Challenges. 27-34 - Wai-Ho Au, Keith C. C. Chan:
Classification with Degree of Membership: A Fuzzy Approach. 35-42 - José L. Balcázar, Yang Dai, Osamu Watanabe:
Provably Fast Training Algorithms for Support Vector Machines. 43-50 - Krishna Bharat, Bay-Wei Chang, Monika Henzinger, Matthias Ruhl:
Who Links to Whom: Mining Linkage between Web Sites. 51-58 - Catherine Blake, Wanda Pratt:
Better Rules, Few Features: A Semantic Approach to Selecting Features from Text. 59-66 - Richard J. Bolton, David J. Hand
:
Significance Tests for Patterns in Continuous Data. 67-74 - Rong Chen, Krishnamoorthy Sivakumar, Hillol Kargupta:
Distributed Web Mining Using Bayesian Networks from Multiple Data Streams. 75-82 - Jong-Sheng Cherng, Mei-Jung Lo:
A Hypergraph Based Clustering Algorithm for Spatial Data Sets. 83-90 - David Maxwell Chickering, Christopher Meek, Robert Rounthwaite:
Efficient Determination of Dynamic Split Points in a Decision Tree. 91-98 - Manoranjan Dash, Kian-Lee Tan, Huan Liu:
Efficient Yet Accurate Clustering. 99-106 - Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Ming Gu, Horst D. Simon
A Min-max Cut Algorithm for Graph Partitioning and Data Clustering. 107-114 - Tapio Elomaa, Juho Rousu:
Preprocessing Opportunities in Optimal Numerical Range Partitioning. 115-122 - Wei Fan, Matthew Miller, Salvatore J. Stolfo, Wenke Lee, Philip K. Chan:
Using Artificial Anomalies to Detect Unknown and Known Network Intrusions. 123-130 - Tom Fawcett:
Using Rule Sets to Maximize ROC Performance. 131-138 - Hichem Frigui, Mohamed Ben Hadj Rhouma:
A Synchronization Based Algorithm for Discovering Ellipsoidal Clusters in Large Datasets. 139-146 - João Gama
Functional Trees for Classification. 147-154 - Floris Geerts
A Tight Upper Bound on the Number of Candidate Patterns. 155-162 - Karam Gouda, Mohammed Javeed Zaki:
Efficiently Mining Maximal Frequent Itemsets. 163-170 - Henner Graubitz, Myra Spiliopoulou, Karsten Winkler:
The DIAsDEM Framework for Converting Domain-Specific Texts into XML Documents with Data Mining Techniques. 171-178 - Valerie Guralnik, George Karypis
A Scalable Algorithm for Clustering Sequential Data. 179-186 - Maria Halkidi, Michalis Vazirgiannis:
Clustering Validity Assessment: Finding the Optimal Partitioning of a Data Set. 187-194 - Xiaofeng He, Chris H. Q. Ding, Hongyuan Zha, Horst D. Simon
Automatic Topic Identification Using Webpage Clustering. 195-202 - Johan Himberg, Kalle Korpiaho, Heikki Mannila, Johanna Tikanmäki, Hannu Toivonen:
Time Series Segmentation for Context Recognition in Mobile Devices. 203-210 - Shoji Hirano, Shusaku Tsumoto:
Indiscernibility Degree of Objects for Evaluating Simplicity of Knowledge in the Clustering Procedure. 211-217 - Tzung-Pei Hong, Yeong-Chyi Lee:
Mining Coverage-Based Fuzzy Rules by Evolutional Computation. 218-224 - Ming-Chuan Hung, Don-Lin Yang:
An Efficient Fuzzy C-Means Clustering Algorithm. 225-232 - Xiaohua Hu:
Using Rough Sets Theory and Database Operations to Construct a Good Ensemble of Classifiers for Data Mining Applications. 233-240 - Hisao Ishibuchi
Fuzzy Data Mining: Effect of Fuzzy Discretization. 241-248 - Chris Jermaine:
The Computational Complexity of High-Dimensional Correlation Search. 249-256 - Mahesh V. Joshi, Vipin Kumar, Ramesh C. Agarwal:
Evaluating Boosting Algorithms to Classify Rare Classes: Comparison and Improvements. 257-264 - Sung Young Jung, Taek-Soo Kim:
An Agglomerative Hierarchical Clustering Using Partial Maximum Array and Incremental Similarity Computation Method. 265-272 - Konstantinos Kalpakis, Dhiral Gada, Vasundhara Puttagunta:
Distance Measures for Effective Clustering of ARIMA Time-Series. 273-280 - Hillol Kargupta, Byung-Hoon Park:
Mining Decision Trees from Data Streams in a Mobile Environment. 281-288 - Eamonn J. Keogh, Selina Chu, David M. Hart, Michael J. Pazzani:
An Online Algorithm for Segmenting Time Series. 289-296 - Thomas Knight, Jon Timmis:
AINE: An Immunological Approach to Data Mining. 297-304 - Marzena Kryszkiewicz:
Concise Representation of Frequent Patterns Based on Disjunction-Free Generators. 305-312 - Michihiro Kuramochi, George Karypis
Frequent Subgraph Discovery. 313-320 - Henry E. Kyburg Jr.:
Statistical Considerations in Learning from Data. 321-328 - Zarrin Langari, Frank Wm. Tompa
Subject Classification in the Oxford English Dictionary. 329-336 - Chang-Hung Lee, Cheng-Ru Lin, Ming-Syan Chen:
On Mining General Temporal Association Rules in a Publication Database. 337-344 - Jung-Won Lee, Kiho Lee, Won Kim:
Preparations for Semantics-Based XML Mining. 345-352 - Beitao Li, Wei-Cheng Lai, Edward Y. Chang, Kwang-Ting Cheng:
Mining Image Features for Efficient Query Processing. 353-360 - Jiuyong Li
Mining the Smallest Association Rule Set for Predictions. 361-368 - Wenmin Li, Jiawei Han, Jian Pei
CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules. 369-376 - Bing Liu, Yiming Ma, Ronnie Lee:
Analyzing the Interestingness of Association Rules from the Temporal Dimension. 377-384 - Gary Livingston, John M. Rosenberg, Bruce G. Buchanan:
Closing the Loop: An Agenda- and Justification-Based Framework for Selecting the Next Discovery Task to Perform. 385-392 - Gary Livingston, John M. Rosenberg, Bruce G. Buchanan:
Closing the Loop: Heuristics for Autonomous Discovery. 393-400 - Wen-Hsiang Lu, Lee-Feng Chien, Hsi-Jian Lee:
Anchor Text Mining for Translation of Web Queries. 401-408 - Sheng Ma, Joseph L. Hellerstein:
Mining Mutually Dependent Patterns. 409-416 - Paul Munteanu, Mohamed Bendou:
The EQ Framework for Learning Equivalence Classes of Bayesian Networks. 417-424 - Steven Noel, Vijay V. Raghavan, Chee-Hung Henry Chu:
Visualizing Association Mining Results through Hierarchical Clusters. 425-432 - Carlos Ordonez, Edward Omiecinski, Levien de Braal, Cesar A. Santana, Norberto F. Ezquerra, José A. Taboada, C. David Cooke, Elizabeth Krawczynska, Ernest V. Garcia:
Mining Constrained Association Rules to Predict Heart Disease. 433-440 - Jian Pei
H-Mine: Hyper-Structure Mining of Frequent Patterns in Large Databases. 441-448 - Chang-Shing Perng, Haixun Wang, Sheng Ma, Joseph L. Hellerstein:
FARM: A Framework for Exploring Mining Spaces with Multiple Attributes. 449-456 - Kimmo Raivio, Olli Simula, Jaana Laiho:
Neural Analysis of Mobile Radio Access Network. 457-466 - Graeme Richards, Victor J. Rayward-Smith:
Discovery of Association Rules in Tabular Data. 465-472 - Lior Rokach, Oded Maimon:
Theory and Applications of Attribute Decomposition. 473-480 - Pierre-Yves Rolland:
FlExPat: Flexible Extraction of Sequential Patterns. 481-488 - Sigal Sahar:
Interestingness PreProcessing. 489-496 - Ying Sai, Yiyu Yao, Ning Zhong:
Data Analysis and Mining in Ordered Information Tables. 497-504 - Masakazu Seno, George Karypis
LPMiner: An Algorithm for Finding Frequent Itemsets Using Length-Decreasing Support Constraint. 505-512 - Joaquim Ferreira da Silva, João Mexia
Document Clustering and Cluster Topic Extraction in Multilingual Corpora. 513-520 - Aixin Sun
Hierarchical Text Classification and Evaluation. 521-528 - François Velin, Pascale Kuntz, Henri Briand:
Web Cartography for Online State Promotion: An Algorithm for Clustering Web Resources. 529-535 - Ching-Yao Wang, Tzung-Pei Hong, Shian-Shyong Tseng:
Maintenance of Sequential Patterns for Record Deletion. 536-541 - Haixun Wang, Philip S. Yu:
SSDT: A Scalable Subspace-Splitting Classifier for Biased Data. 542-549 - Wei Wang, Jiong Yang, Philip S. Yu:
Meta-patterns: Revealing Hidden Periodic Patterns. 550-557 - Virginia Wheway:
Using Boosting to Simplify Classification Models. 558-565 - Ning Zhong, Y. Y. Yao, Muneaki Ohshima, Setsuo Ohsuga:
Interestingness, Peculiarity, and Multi-Database Mining. 566-576
Posters
- Fernando Alonso, Juan Pedro Caraça-Valente
Discovering Similar Patterns for Characterising Time Series in a Medical Domain. 577-579 - Nitesh V. Chawla, Steven Eschrich, Lawrence O. Hall:
Creating Ensembles of Classifiers. 580-581 - Jie Chen, Haiying Li, Shiwei Tang:
Association Rules Enhanced Classification of Underwater Acoustic Signal. 582-583 - June-Suh Cho, Nabil R. Adam:
Efficient Splitting Rules Based on the Probabilities of Pre-assigned Intervals. 584-585 - Honghua Dai, Xiaoshu Hang, Gang Li:
Inexact Field Learning: An Approach to Induce High Quality Rules from Low Quality Data. 586-588 - Carlotta Domeniconi, Dimitrios Gunopulos:
Incremental Support Vector Machine Construction. 589-592 - Wolfgang Gaul, Lars Schmidt-Thieme:
Mining Generalized Association Rules for Sequential and Path Data. 593-596 - Rayid Ghani:
Combining Labeled and Unlabeled Data for Text Classification with a Large Number of Categories. 597-598 - Daniel Gillblad, Anders Holst:
Dependency Derivation in Industrial Process Data. 599-602 - Sherri K. Harms
Discovering Representative Episodal Association Rules from Event Sequences Using Frequent Closed Episode Sets and Event Constraints. 603-606 - Andreas Hotho, Alexander Maedche, Steffen Staab:
Text Clustering Based on Good Aggregations. 607-608 - Hasan M. Jamil
Ad Hoc Association Rule Mining as SQL3 Queries. 609-612 - Viviane Crestana-Jensen, Nandit Soparkar:
Heuristic Optimization for Decentralized Frequent Itemset Counting. 613-614 - Gang Li, Fu Tong, Honghua Dai:
Evolutionary Structure Learning Algorithm for Bayesian Network and Penalized Mutual Information Metric. 615-616 - Xu Liang, Yao Liang:
Applications of Data Mining in Hydrology. 617-620 - Zhiyong Liu, Lei Xu:
RPCL-Based Local PCA Algorithm. 621-622 - Manolis Maragoudakis, Katia Kermanidis, Nikos Fakotakis, George K. Kokkinakis:
Learning Automatic Acquisition of Subcategorization Frames Using Bayesian Inference and Support Vector Machines. 623-625 - Petri Myllymäki, Tomi Silander, Henry Tirri, Pekka Uronen:
Bayesian Data Mining on the Web with B-Course. 626-629 - Tadashi Nomoto, Yuji Matsumoto:
An Experimental Comparison of Supervised and Unsupervised Approaches to Text Summarization. 630-632 - Carlos Ordonez, Edward Omiecinski, Norberto F. Ezquerra:
A Fast Algorithm to Cluster High Dimensional Basket Data. 633-636 - Jürgen Paetz:
Metric Rule Generation with Septic Shock Patient Data. 637-638 - Viet Phan Luong:
The Representative Basis for Association Rules. 639-640 - Stefan Rüping:
Incremental Learning with Support Vector Machines. 641-642 - Guillermo Sánchez-Díaz, José Ruiz-Shulcloper:
A Clustering Method for Very Large Mixed Data Sets. 643-644 - Tobias Scheffer, Christian Decomain, Stefan Wrobel:
Mining the Web with Active Hidden Markov Models. 645-646 - Pascal Soucy, Guy W. Mineau:
A Simple KNN Algorithm for Text Categorization. 647-648 - Sam Steingold, Richard Wherry, Gregory Piatetsky-Shapiro:
Measuring Real-Time Predictive Models. 649-650 - Fengzhan Tian, Hongwei Zhang, Yuchang Lu, Chunyi Shi:
Incremental Learning of Bayesian Networks with Hidden Variables. 651-652 - Fan-Chen Tseng, Ching-Chi Hsu, Henry Chen:
Mining Frequent Closed Itemsets with the Frequent Pattern List. 653-654 - Hui Wang, Ivo Düntsch, David A. Bell, Dayou Liu:
Classification through Maximizing Density. 655-656 - Lei Wang, Licheng Jiao
An Immune Neural Network Used for Classification. 657-658 - Xiong Wang:
alpha-Surface and Its Application to Mining Protein Data. 659-662 - Show-Jane Yen, Yue-Shi Lee:
An Efficient Data Mining Technique for Discovering Interesting Sequential Patterns. 663-664 - Osmar R. Zaïane, Mohammad El-Hajj, Paul Lu:
Fast Parallel Association Rule Mining without Candidacy Generation. 665-668 - Bernard Zenko, Ljupco Todorovski, Saso Dzeroski:
A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods. 669-670 - Du Zhang, Quoc Luan Ha, Meiliu Lu:
Mining California Vital Statistics Data. 671-672 - Qinghua Zou, Wesley W. Chu, David B. Johnson, Henry Chiu:
A Pattern Decomposition (PD) Algorithm for Finding All Frequent Patterns in Large Datasets. 673-674
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