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Semantic Scholar1st 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. 3-10Aijun An, Yuanyuan Wang:
Comparisons of Classification Methods for Screening Potential Compounds. 11-18Michael Anderson:
Knowledge Discovery from Diagrammatically Represented Data. 19-26Suhail Ansari, Ron Kohavi, Llew Mason, Zijian Zheng:
Integrating E-Commerce and Data Mining: Architecture and Challenges. 27-34Wai-Ho Au, Keith C. C. Chan:
Classification with Degree of Membership: A Fuzzy Approach. 35-42José L. Balcázar, Yang Dai, Osamu Watanabe:
Provably Fast Training Algorithms for Support Vector Machines. 43-50Krishna Bharat, Bay-Wei Chang, Monika Rauch Henzinger, Matthias Ruhl:
Who Links to Whom: Mining Linkage between Web Sites. 51-58Catherine Blake, Wanda Pratt:
Better Rules, Few Features: A Semantic Approach to Selecting Features from Text. 59-66Richard J. Bolton, David J. Hand:
Significance Tests for Patterns in Continuous Data. 67-74Rong Chen, Krishnamoorthy Sivakumar, Hillol Kargupta:
Distributed Web Mining Using Bayesian Networks from Multiple Data Streams. 75-82Jong-Sheng Cherng, Mei-Jung Lo:
A Hypergraph Based Clustering Algorithm for Spatial Data Sets. 83-90David Maxwell Chickering, Christopher Meek, Robert Rounthwaite:
Efficient Determination of Dynamic Split Points in a Decision Tree. 91-98Manoranjan Dash, Kian-Lee Tan, Huan Liu:
Efficient Yet Accurate Clustering. 99-106Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Ming Gu, Horst D. Simon:
A Min-max Cut Algorithm for Graph Partitioning and Data Clustering. 107-114Tapio Elomaa, Juho Rousu:
Preprocessing Opportunities in Optimal Numerical Range Partitioning. 115-122Wei Fan, Matthew Miller, Salvatore J. Stolfo, Wenke Lee, Philip K. Chan:
Using Artificial Anomalies to Detect Unknown and Known Network Intrusions. 123-130Tom Fawcett:
Using Rule Sets to Maximize ROC Performance. 131-138Hichem Frigui, Mohamed Ben Hadj Rhouma:
A Synchronization Based Algorithm for Discovering Ellipsoidal Clusters in Large Datasets. 139-146João Gama:
Functional Trees for Classification. 147-154Floris Geerts, Bart Goethals, Jan Van den Bussche:
A Tight Upper Bound on the Number of Candidate Patterns. 155-162Karam Gouda, Mohammed Javeed Zaki:
Efficiently Mining Maximal Frequent Itemsets. 163-170Henner Graubitz, Myra Spiliopoulou, Karsten Winkler:
The DIAsDEM Framework for Converting Domain-Specific Texts into XML Documents with Data Mining Techniques. 171-178Valerie Guralnik, George Karypis:
A Scalable Algorithm for Clustering Sequential Data. 179-186Maria Halkidi, Michalis Vazirgiannis:
Clustering Validity Assessment: Finding the Optimal Partitioning of a Data Set. 187-194Xiaofeng He, Chris H. Q. Ding, Hongyuan Zha, Horst D. Simon:
Automatic Topic Identification Using Webpage Clustering. 195-202Johan Himberg, Kalle Korpiaho, Heikki Mannila, Johanna Tikanmäki, Hannu Toivonen:
Time Series Segmentation for Context Recognition in Mobile Devices. 203-210Shoji Hirano, Shusaku Tsumoto:
Indiscernibility Degree of Objects for Evaluating Simplicity of Knowledge in the Clustering Procedure. 211-217Tzung-Pei Hong, Yeong-Chyi Lee:
Mining Coverage-Based Fuzzy Rules by Evolutional Computation. 218-224Ming-Chuan Hung, Don-Lin Yang:
An Efficient Fuzzy C-Means Clustering Algorithm. 225-232Xiaohua Hu:
Using Rough Sets Theory and Database Operations to Construct a Good Ensemble of Classifiers for Data Mining Applications. 233-240Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima:
Fuzzy Data Mining: Effect of Fuzzy Discretization. 241-248Chris Jermaine:
The Computational Complexity of High-Dimensional Correlation Search. 249-256Mahesh V. Joshi, Vipin Kumar, Ramesh C. Agarwal:
Evaluating Boosting Algorithms to Classify Rare Classes: Comparison and Improvements. 257-264Sung Young Jung, Taek-Soo Kim:
An Agglomerative Hierarchical Clustering Using Partial Maximum Array and Incremental Similarity Computation Method. 265-272Konstantinos Kalpakis, Dhiral Gada, Vasundhara Puttagunta:
Distance Measures for Effective Clustering of ARIMA Time-Series. 273-280Hillol Kargupta, Byung-Hoon Park:
Mining Decision Trees from Data Streams in a Mobile Environment. 281-288Eamonn J. Keogh, Selina Chu, David M. Hart, Michael J. Pazzani:
An Online Algorithm for Segmenting Time Series. 289-296Thomas Knight, Jon Timmis:
AINE: An Immunological Approach to Data Mining. 297-304Marzena Kryszkiewicz:
Concise Representation of Frequent Patterns Based on Disjunction-Free Generators. 305-312Michihiro Kuramochi, George Karypis:
Frequent Subgraph Discovery. 313-320Henry E. Kyburg Jr.:
Statistical Considerations in Learning from Data. 321-328Zarrin Langari, Frank Wm. Tompa:
Subject Classification in the Oxford English Dictionary. 329-336Chang-Hung Lee, Cheng-Ru Lin, Ming-Syan Chen:
On Mining General Temporal Association Rules in a Publication Database. 337-344Jung-Won Lee, Kiho Lee, Won Kim:
Preparations for Semantics-Based XML Mining. 345-352Beitao Li, Wei-Cheng Lai, Edward Y. Chang, Kwang-Ting Cheng:
Mining Image Features for Efficient Query Processing. 353-360Jiuyong Li, Hong Shen, Rodney W. Topor:
Mining the Smallest Association Rule Set for Predictions. 361-368Wenmin Li, Jiawei Han, Jian Pei:
CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules. 369-376Bing Liu, Yiming Ma, Ronnie Lee:
Analyzing the Interestingness of Association Rules from the Temporal Dimension. 377-384Gary Livingston, John M. Rosenberg, Bruce G. Buchanan:
Closing the Loop: An Agenda- and Justification-Based Framework for Selecting the Next Discovery Task to Perform. 385-392Gary Livingston, John M. Rosenberg, Bruce G. Buchanan:
Closing the Loop: Heuristics for Autonomous Discovery. 393-400Wen-Hsiang Lu, Lee-Feng Chien, Hsi-Jian Lee:
Anchor Text Mining for Translation of Web Queries. 401-408Sheng Ma, Joseph L. Hellerstein:
Mining Mutually Dependent Patterns. 409-416Paul Munteanu, Mohamed Bendou:
The EQ Framework for Learning Equivalence Classes of Bayesian Networks. 417-424Steven Noel, Vijay V. Raghavan, Chee-Hung Henry Chu:
Visualizing Association Mining Results through Hierarchical Clusters. 425-432Carlos 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. 433-440Jian Pei, Jiawei Han, Hongjun Lu, Shojiro Nishio, Shiwei Tang, Dongqing Yang:
H-Mine: Hyper-Structure Mining of Frequent Patterns in Large Databases. 441-448Chang-Shing Perng, Haixun Wang, Sheng Ma, Joseph L. Hellerstein:
FARM: A Framework for Exploring Mining Spaces with Multiple Attributes. 449-456Kimmo Raivio, Olli Simula, Jaana Laiho:
Neural Analysis of Mobile Radio Access Network. 457-466Graeme Richards, Victor J. Rayward-Smith:
Discovery of Association Rules in Tabular Data. 465-472Lior Rokach, Oded Maimon:
Theory and Applications of Attribute Decomposition. 473-480Pierre-Yves Rolland:
FlExPat: Flexible Extraction of Sequential Patterns. 481-488Sigal Sahar:
Interestingness PreProcessing. 489-496Ying Sai, Yiyu Yao, Ning Zhong:
Data Analysis and Mining in Ordered Information Tables. 497-504Masakazu Seno, George Karypis:
LPMiner: An Algorithm for Finding Frequent Itemsets Using Length-Decreasing Support Constraint. 505-512Joaquim Ferreira da Silva, João Mexia, Carlos Agra Coelho, José Gabriel Pereira Lopes:
Document Clustering and Cluster Topic Extraction in Multilingual Corpora. 513-520Aixin Sun, Ee-Peng Lim:
Hierarchical Text Classification and Evaluation. 521-528François Velin, Pascale Kuntz, Henri Briand:
Web Cartography for Online State Promotion: An Algorithm for Clustering Web Resources. 529-535Ching-Yao Wang, Tzung-Pei Hong, Shian-Shyong Tseng:
Maintenance of Sequential Patterns for Record Deletion. 536-541Haixun Wang, Philip S. Yu:
SSDT: A Scalable Subspace-Splitting Classifier for Biased Data. 542-549Wei Wang, Jiong Yang, Philip S. Yu:
Meta-patterns: Revealing Hidden Periodic Patterns. 550-557Virginia Wheway:
Using Boosting to Simplify Classification Models. 558-565Ning Zhong, Y. Y. Yao, Muneaki Ohshima, Setsuo Ohsuga:
Interestingness, Peculiarity, and Multi-Database Mining. 566-576
Posters
Fernando Alonso, Juan Pedro Caraça-Valente, Loïc Martínez, César Montes:
Discovering Similar Patterns for Characterising Time Series in a Medical Domain. 577-579Nitesh V. Chawla, Steven Eschrich, Lawrence O. Hall:
Creating Ensembles of Classifiers. 580-581Jie Chen, Haiying Li, Shiwei Tang:
Association Rules Enhanced Classification of Underwater Acoustic Signal. 582-583June-Suh Cho, Nabil R. Adam:
Efficient Splitting Rules Based on the Probabilities of Pre-assigned Intervals. 584-585Honghua Dai, Xiaoshu Hang, Gang Li:
Inexact Field Learning: An Approach to Induce High Quality Rules from Low Quality Data. 586-588Carlotta Domeniconi, Dimitrios Gunopulos:
Incremental Support Vector Machine Construction. 589-592Wolfgang Gaul, Lars Schmidt-Thieme:
Mining Generalized Association Rules for Sequential and Path Data. 593-596Rayid Ghani:
Combining Labeled and Unlabeled Data for Text Classification with a Large Number of Categories. 597-598Daniel Gillblad, Anders Holst:
Dependency Derivation in Industrial Process Data. 599-602Sherri K. Harms, Jitender S. Deogun, Jamil Saquer, Tsegaye Tadesse:
Discovering Representative Episodal Association Rules from Event Sequences Using Frequent Closed Episode Sets and Event Constraints. 603-606Andreas Hotho, Alexander Maedche, Steffen Staab:
Text Clustering Based on Good Aggregations. 607-608Hasan M. Jamil:
Ad Hoc Association Rule Mining as SQL3 Queries. 609-612Viviane Crestana-Jensen, Nandit Soparkar:
Heuristic Optimization for Decentralized Frequent Itemset Counting. 613-614Gang Li, Fu Tong, Honghua Dai:
Evolutionary Structure Learning Algorithm for Bayesian Network and Penalized Mutual Information Metric. 615-616Xu Liang, Yao Liang:
Applications of Data Mining in Hydrology. 617-620Zhiyong Liu, Lei Xu:
RPCL-Based Local PCA Algorithm. 621-622Manolis Maragoudakis, Katia Kermanidis, Nikos Fakotakis, George K. Kokkinakis:
Learning Automatic Acquisition of Subcategorization Frames Using Bayesian Inference and Support Vector Machines. 623-625Petri Myllymäki, Tomi Silander, Henry Tirri, Pekka Uronen:
Bayesian Data Mining on the Web with B-Course. 626-629Tadashi Nomoto, Yuji Matsumoto:
An Experimental Comparison of Supervised and Unsupervised Approaches to Text Summarization. 630-632Carlos Ordonez, Edward Omiecinski, Norberto F. Ezquerra:
A Fast Algorithm to Cluster High Dimensional Basket Data. 633-636Jürgen Paetz:
Metric Rule Generation with Septic Shock Patient Data. 637-638Viet Phan Luong:
The Representative Basis for Association Rules. 639-640Stefan Rüping:
Incremental Learning with Support Vector Machines. 641-642Guillermo Sánchez-Díaz, José Ruiz-Shulcloper:
A Clustering Method for Very Large Mixed Data Sets. 643-644Tobias Scheffer, Christian Decomain, Stefan Wrobel:
Mining the Web with Active Hidden Markov Models. 645-646Pascal Soucy, Guy W. Mineau:
A Simple KNN Algorithm for Text Categorization. 647-648Sam Steingold, Richard Wherry, Gregory Piatetsky-Shapiro:
Measuring Real-Time Predictive Models. 649-650Fengzhan Tian, Hongwei Zhang, Yuchang Lu, Chunyi Shi:
Incremental Learning of Bayesian Networks with Hidden Variables. 651-652Fan-Chen Tseng, Ching-Chi Hsu, Henry Chen:
Mining Frequent Closed Itemsets with the Frequent Pattern List. 653-654Hui Wang, Ivo Düntsch, David A. Bell, Dayou Liu:
Classification through Maximizing Density. 655-656Lei Wang, Licheng Jiao:
An Immune Neural Network Used for Classification. 657-658Xiong Wang:
alpha-Surface and Its Application to Mining Protein Data. 659-662Show-Jane Yen, Yue-Shi Lee:
An Efficient Data Mining Technique for Discovering Interesting Sequential Patterns. 663-664Osmar R. Zaïane, Mohammad El-Hajj, Paul Lu:
Fast Parallel Association Rule Mining without Candidacy Generation. 665-668Bernard Zenko, Ljupco Todorovski, Saso Dzeroski:
A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods. 669-670Du Zhang, Quoc Luan Ha, Meiliu Lu:
Mining California Vital Statistics Data. 671-672Qinghua Zou, Wesley W. Chu, David B. Johnson, Henry Chiu:
A Pattern Decomposition (PD) Algorithm for Finding All Frequent Patterns in Large Datasets. 673-674
last updated on 2019-11-12 22:40 CET by the dblp team
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