• Skip to main content
  • Skip to primary sidebar
AAAI

AAAI

Association for the Advancement of Artificial Intelligence

    • AAAI

      AAAI

      Association for the Advancement of Artificial Intelligence

  • About AAAIAbout AAAI
    • News
    • Officers and Committees
    • Staff
    • Bylaws
    • Awards
      • Fellows Program
      • Classic Paper Award
      • Dissertation Award
      • Distinguished Service Award
      • Allen Newell Award
      • Outstanding Paper Award
      • AI for Humanity Award
      • Feigenbaum Prize
      • Patrick Henry Winston Outstanding Educator Award
      • Engelmore Award
      • AAAI ISEF Awards
      • Senior Member Status
      • Conference Awards
    • Partnerships
    • Resources
    • Mailing Lists
    • Past Presidential Addresses
    • AAAI 2025 Presidential Panel on the Future of AI Research
    • Presidential Panel on Long-Term AI Futures
    • Past Policy Reports
      • The Role of Intelligent Systems in the National Information Infrastructure (1995)
      • A Report to ARPA on Twenty-First Century Intelligent Systems (1994)
    • Logos
  • aaai-icon_ethics-diversity-line-yellowEthics & Diversity
  • Conference talk bubbleConferences & Symposia
    • AAAI Conference
    • AIES AAAI/ACM
    • AIIDE
    • EAAI
    • HCOMP
    • IAAI
    • ICWSM
    • Spring Symposia
    • Summer Symposia
    • Fall Symposia
    • Code of Conduct for Conferences and Events
  • PublicationsPublications
    • AI Magazine
    • Conference Proceedings
    • AAAI Publication Policies & Guidelines
    • Request to Reproduce Copyrighted Materials
    • Contribute
    • Order Proceedings
  • aaai-icon_ai-magazine-line-yellowAI Magazine
  • MembershipMembership
    • Member Login
    • Chapters

  • Career CenterAI Jobs
  • aaai-icon_ai-topics-line-yellowAITopics
  • aaai-icon_contact-line-yellowContact

  • Twitter
  • Facebook
  • LinkedIn
Home / Proceedings / Proceedings of the Third International Conference on Knowledge Discovery and Data Mining /

Book One

All Contents

  • Large Scale Data Mining: Challenges and Responses

    Jaturon Chattratichat, John Darlington, Moustafa Ghanem, Yike Guo, Harald Huning, Martin Kohler, Janjao Sutiwaraphun, Hing Wing To, Dan Yang

    PDF
  • Scaling Up Inductive Algorithms: An Overview

    Foster Provost, Venkateswarlu Kolluri

    PDF
  • Development of Multi-Criteria Metrics for Evaluation of Data Mining Algorithms

    Gholamreza Nakhaeizadeh, Alexander Schnabl

    PDF
  • Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation

    John Aronis, Foster Provost

    PDF
  • GA-based Rule Enhancement in Concept Learning

    Jukka Hekanaho, Turku Center for Computer Science and Åbo Akademi University, Finland

    PDF
  • Learning to Extract Text-based Information from the World Wide Web

    Stephen Soderland

    PDF
  • Clustering Sequences of Complex Objects

    Alain Ketterlin

    PDF
  • Anytime Exploratory Data Analysis for Massive Data Sets

    Padhraic Smyth, David Wolpert

    PDF
  • Partial Classification Using Association Rules

    Kamal Ali and Stefanos Manganaris and Ramakrishnan Srikant

    PDF
  • Mining Generalized Term Associations: Count Propagation Algorithm

    Jonghyun Kahng, Wen-Hsiang Kevin Liao, and Dennis McLeod, University of Southern California

    PDF
  • Discriminative Versus Informative Learning

    Y. Dan Rubinstein and Trevor Hastie, Stanford University

    PDF
  • Integrating and Mining Distributed Customer Databases

    Ira Haimowitz, Ozden Gur-Ali, Henry Schwarz

    PDF
  • Knowledge = Concepts: a Harmful Equation

    Jan M. Zytkow

    PDF
  • Discovery of Actionable Patterns in Databases: The Action Hierarchy Approach

    Gediminas Adomavicius, New York University and Alexander Tuzhilin, Stern School of Business, New York City University

    PDF
  • Scalable, Distributed Data Mining – An Agent Architecture

    Hillol Kargupta, Ilker Hamzaoglu, Brian Stafford

    PDF
  • Visualizing Bagged Decision Trees

    Sunil Rao, William J. E. Potts,

    PDF
  • Using Artificial Intelligence Planning to Automate Science Data Analysis for Large Image Databases

    Steve Chien, Forest Fisher, Helen Mortensen, Edisanter Lo, Ronald Greeley

    PDF
  • Visualization Techniques to Explore Data Mining Results for Document Collections

    Ronen Feldman and Willi Kloesgen and Amir Zilberstein

    PDF
  • An Efficient Algorithm for the Incremental Updation of Association Rules in Large Databases

    Shiby Thomas, Sreenath Bodagala, Khaled Alsabti, Sanjay Ranka

    PDF
  • JAM: Java Agents for Meta-Learning over Distributed Databases

    Salvatore Stolfo, Andreas L. Prodromidis, Shelley Tselepis, Wenke Lee, Dave W. Fan, Philip K. Chan

    PDF
  • Brute-Force Mining of High-Confidence Classification Rules

    Roberto J. Bayarod Jr.

    PDF
  • Zeta: A Global Method for Discretization of Continuous Variables

    K. M. Ho, P. D. Scott

    PDF
  • Proposal and Empirical Comparison of a Parallelizable Distance-Based Discretization Method

    Jesus Cerquides, Ramon Lopez de Mantaras

    PDF
  • Mining Association Rules with Item Constraints

    Ramakrishnan Srikant, Quoc Vu, Rakesh Agrawal

    PDF
  • Metarule-Guided Mining of Multi-Dimensional Association Rules Using Data Cubes

    Micheline Kamber, Jiawei Han, Jenny Y. Chiang

    PDF
  • Autonomous Discovery of Reliable Exception Rules

    Einoshin Suzuki

    PDF
  • Analysis and Visualization of Classifier Performance: Comparison under Imprecise Class and Cost Distributions

    Foster Provost, Tom Fawcett

    PDF
  • Target-Independent Mining For Scientific Data: Capturing Transients and Trends for Phenomena Mining

    Thomas H. Hinke, John Rushing, Heggere Ranganath and Sara J. Graves

    PDF
  • New Algorithms for Fast Discovery of Association Rules

    M. J. Zaki, S. Parthasarathy, M. Ogihara, and W. Li

    PDF
  • MineSet: An Integrated System for Data Mining

    Cliff Brunk, James Kelly, Ron Kohavi

    PDF
  • Detecting Atmospheric Regimes Using Cross-Validated Clustering

    Padhraic Smyth, Michael Ghil, Kayo Ide, Joe Roden, Andrew Fraser

    PDF
  • Image Feature Reduction through Spoiling: Its Application to Multiple Matched Filters for Focus of Attention

    Timothy M. Stough, Carla E. Brodley

    PDF
  • A Probabilistic Approach to Fast Pattern Matching in Time Series Databases

    Eamonn Keogh, Padhraic Smyth

    PDF
  • Fast Robust Visual Data Mining

    Ted Mihalisin, John Timlin

    PDF
  • Applying Data Mining and Machine Learning Techniques to Submarine Intelligence Analysis

    Ulla Bergsten, Johan Schubert, Per Svensson

    PDF
  • A Dataset Decomposition Approach to Data Mining and Machine Discovery

    Blaz Zupan, Marko Bohanec, Ivan Bratko, and Bojan Cestnik

    PDF
  • Adjusting for Multiple Comparisons in Decision Tree Pruning

    David Jensen, Matt Schmill

    PDF
  • Process-Based Database Support for the Early Indicator Method

    Christoph Breitner, Jörg Schlösser, Rüdiger Wirth

    PDF
  • Mining for Causes of Cancer: Machine Learning Experiments at Various Levels of Detail

    Stefan Kramer and Bernhard Pfahringer and Christoph Helma

    PDF
  • Improving Scalability in a Scientific Discovery System by Exploiting Parallelism

    Gehad Galal, Diane J. Cook, Lawrence B. Holder

    PDF
  • Selecting Features by Vertical Compactness of Data

    Ke Wang and Suman Sundaresh

    PDF
  • Schema Discovery for Semistructured Data

    Ke Wang and Huiqing Liu

    PDF
  • Maximal Association Rules: A New Tool for Mining for Keyword Co-Occurrences in Document Collections

    Ronen Feldman, Yonatan Aumann, Amihood Amir, Amir Zilberstein, Willi Kloesgen

    PDF
  • Mining Multivariate Time-Series Sensor Data to Discover Behavior Envelopes

    Dennis DeCoste

    PDF
  • Keso: Minimizing Database Interaction

    Siebes Arno Martin L. Kersten

    PDF
  • Automated Discovery of Active Motifs in Three Dimensional Molecules

    Xiong Wang, Jason T. L. Wang, Dennis Shasha, Bruce Shapiro, Sitaram Dikshitulu, Isidore Rigoutsos and Kaizhong Zhang

    PDF
  • An Interactive Visualization Environment for Data Exploration

    Mark Derthick, John Kolojejchick, Steven F. Roth

    PDF
  • SIPping from the Data Firehose

    George H. John, IBM Almaden Research Center and Brian Lent, Stanford University

    PDF
  • A Visual Interactive Framework for Attribute Discretization

    Ramesh Subramonian, Ramana Venkata, and Joyce Chen, Intel Corporation

    PDF
  • KDD Process Planning

    Ning Zhong, Yamaguchi University, Japan; Chunnian Liu, Beijing Polytechnic University, China; Yoshitsugu Kakemoto, The University of Tokyo, Japan; Setsuo Ohsuga, Waseda University, Japan

    PDF
  • Using General Impressions to Analyze Discovered Classification Rules

    Bing Liu, Wynne Hsu and Shu Chen

    PDF
  • A Guided Tour through the Data Mining Jungle

    Robert Engels, University of Karlsruhe, Germany; Guido Lindner, Daimler Benz AG, Germany; Rudi Studer, University of Karlsruhe, Germany

    PDF
  • From Large to Huge: A Statistician’s Reactions to KDD and Data Mining

    Peter J. Huber

    PDF
  • Bayesian Inference for Identifying Solar Active Regions

    Michael Turmon, Saleem Mukhtar and Judit Pap

    PDF
  • Beyond Concise and Colorful: Learning Intelligible Rules

    Michael J. Pazzani, Subramani Mani, W. Rodman Shankle

    PDF
  • Fast and Intuitive Clustering of Web Documents

    Oren Zamir, Oren Etzioni, Omid Madani, and Richard M. Karp, University of Washington

    PDF
  • A Unified Notion of Outliers: Properties and Computation

    Edwin M. Knorr, Raymond T. Ng

    PDF
  • Optimal Multiple Intervals Discretization of Continuous Attributes for Supervised Learning

    D. A. Zighed and R. Rakotomalala and F. Feschet

    PDF
  • Computing Optimized Rectilinear Regions for Association Rules

    Kunikazu Yoda, Takeshi Fukuda, Yasuhiko Morimoto, Shinichi Morishita, Takeshi Tokuyama

    PDF
  • Fast Committee Machines for Regression and Classification

    Harris Drucker

    PDF
  • Density-Connected Sets and their Application for Trend Detection in Spatial Databases

    Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu

    PDF
  • Why Does Bagging Work? A Bayesian Account and its Implications

    Pedro Domingos

    PDF
  • Knowledge Discovery in Integrated Call Centers: A Framework for Effective Customer-Driven Marketing

    Paul Xia

    PDF
  • Discovering Trends in Text Databases

    Brian Lent, Rakesh Agrawal, Ramakrishnan Srikant

    PDF
  • Deep Knowledge Discovery from Natural Language Texts

    Udo Hahn and Klemens Schnattinger, Freiburg University, Germany

    PDF

Primary Sidebar