vldb_2000_elementary.txt

利用lwp：：get写的

<proceedings><paper><title>Ordering Information, Conference Organizers, Program Committees, Additional Reviewers, Additional Demonstrations Reviewers, Sponsors, VLDB Endowment, Preface, Foreword.</title><year>2000</year><conference>International Conference on Very Large Data Bases</conference><citation></citation><abstract></abstract></paper><paper><title>Practical Applications of Triggers and Constraints: Success and Lingering Issues (10-Year Award).</title><author><AuthorName>Stefano Ceri</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>Roberta Cochrane</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>Jennifer Widom</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><year>2000</year><conference>International Conference on Very Large Data Bases</conference><citation><name>On Maintaining Priorities in a Production Rule System.</name><name>The Asilomar Report on Database Research.</name><name>Materialized Views in Oracle.</name><name>Designing Database Applications with Objects and Rules: The IDEA Methodology.</name><name>Integrating Triggers and Declarative Constraints in SQL Database Sytems.</name><name>Deriving Production Rules for Constraint Maintainance.</name><name>Deriving Production Rules for Incremental View Maintenance.</name><name>Managing Semantic Heterogeneity with Production Rules and Persistent Queues.</name><name>Organizing Long-Running Activities with Triggers and Transactions.</name><name>Functional Specifications of Subsystem for Database Integrity.</name><name>Rule Condition Testing and Action Execution in Ariel.</name><name>Semantic Integrity in a Relational Data Base System.</name><name>A Run-Time Execution Model for Referential Integrity Maintenance.</name><name>Extensions to Starburst: Objects, Types, Functions, and Rules.</name><name>Maintenance of Automatic Summary Tables.</name><name>The Postgres Next Generation Database Management System.</name><name>Promises and Realities of Active Database Systems.</name><name>Third-Generation Database System Manifesto - The Committee for Advanced DBMS Function.</name><name>Implementation of Integrity Constraints and Views by Query Modification.</name><name>A First Course in Database Systems.</name><name>Active Database Systems: Triggers and Rules For Advanced Database Processing.</name></citation><abstract></abstract></paper><paper><title>Biodiversity Informatics: The Challenge of Rapid Development, Large Databases, and Complex Data (Keynote).</title><author><AuthorName>Meridith A. Lane</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>James L. Edwards</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>Ebbe Nielsen</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><year>2000</year><conference>International Conference on Very Large Data Bases</conference><citation><name></name></citation><abstract></abstract></paper><paper><title>Toto, We're Not in Kansas Anymore: On Transitioning from Research to the Real (Invited Industrial Talk).</title><author><AuthorName>Michael J. Carey</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><year>2000</year><conference>International Conference on Very Large Data Bases</conference><citation></citation><abstract></abstract></paper><paper><title>Rethinking Database System Architecture: Towards a Self-Tuning RISC-Style Database System.</title><author><AuthorName>Surajit Chaudhuri</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>Gerhard Weikum</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><year>2000</year><conference>International Conference on Very Large Data Bases</conference><citation><name>Distributed Processing over Stand-alone Systems and Applications.</name><name>The Asilomar Report on Database Research.</name><name>Implementation Concepts for an Extensible Data Model and Data Language.</name><name>Towards Automated Performance Tuning for Complex Workloads.</name><name>The Architecture of the EXODUS Extensible DBMS.</name><name>Of Objects and Databases: A Decade of Turmoil.</name><name>An Efficient Cost-Driven Index Selection Tool for Microsoft SQL Server.</name><name>Automated Selection of Materialized Views and Indexes in SQL Databases.</name><name>Querying Multiple Features of Groups in Relational Databases.</name><name>Letter from the Special Issue Editor.</name><name>Bundling: Towards a New Construction Paradigm for Persistent Systems.</name><name>The EXODUS Optimizer Generator.</name><name>The Value of Merge-Join and Hash-Join in SQL Server.</name><name>Starburst Mid-Flight: As the Dust Clears.</name><name>The DASDBS Project: Objectives, Experiences, and Future Prospects.</name><name>Database Tuning - A Principled Approach.
 Prentice-Hall 1992, ISBN 0-13-205246-6</name><name>Strategic Directions in Database Systems - Breaking Out of the Box.</name><name>The Implementation of Postgres.</name><name>The COMFORT Automatic Tuning Project, Invited Project Review.</name></citation><abstract></abstract></paper><paper><title>PicoDMBS: Scaling Down Database Techniques for the Smartcard.</title><author><AuthorName>Christophe Bobineau</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>Luc Bouganim</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>Philippe Pucheral</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>Patrick Valduriez</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><year>2000</year><conference>International Conference on Very Large Data Bases</conference><citation><name>Memory-Adaptive Scheduling for Large Query Execution.</name><name>Query Evaluation Techniques for Large Databases.</name><name>The New Database Imperatives.</name><name>Relational Queries in a Domain Based DBMS.</name><name>Efficient Main Memory Data Management Using the DBGraph Storage Model.</name><name>Join Indices.</name></citation><abstract></abstract></paper><paper><title>The 3W Model and Algebra for Unified Data Mining.</title><author><AuthorName>Theodore Johnson</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>Laks V. S. Lakshmanan</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>Raymond T. Ng</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><year>2000</year><conference>International Conference on Very Large Data Bases</conference><citation><name>Online Generation of Association Rules.</name><name>Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications.</name><name>Mining Association Rules between Sets of Items in Large Databases.</name><name>Fast Algorithms for Mining Association Rules in Large Databases.</name><name>OPTICS: Ordering Points To Identify the Clustering Structure.</name><name>The R*-Tree: An Efficient and Robust Access Method for Points and Rectangles.</name><name>Relational Expressive Power of Constraint Query Languages.</name><name>Beyond Market Baskets: Generalizing Association Rules to Correlations.</name><name>Data Mining and Database Systems: Where is the Intersection?</name><name>SPIRIT: Sequential Pattern Mining with Regular Expression Constraints.</name><name>Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total.</name><name>R-Trees: A Dynamic Index Structure for Spatial Searching.</name><name>Complete Geometric Query Languages.</name><name>Discovery of Multiple-Level Association Rules from Large Databases.</name><name>Online Association Rule Mining.</name><name>A Database Perspective on Knowledge Discovery.</name><name>What can Hierarchies do for Data Warehouses?</name><name>Fast Computation of 2-Dimensional Depth Contours.</name><name>Constraint Query Languages.</name><name>Finding Interesting Rules from Large Sets of Discovered Association Rules.</name><name>Optimization of Constrained Frequent Set Queries with 2-variable Constraints.</name><name>Discovery of Frequent Episodes in Event Sequences.</name><name>A New SQL-like Operator for Mining Association Rules.</name><name>Efficient and Effective Clustering Methods for Spatial Data Mining.</name><name>Exploratory Mining and Pruning Optimizations of Constrained Association Rules.</name><name>Towards a Theory of Spatial Database Queries.</name><name>Induction of Decision Trees.</name><name>Integrating Mining with Relational Database Systems: Alternatives and Implications.</name><name>Scalable Techniques for Mining Causal Structures.</name><name>Query Flocks: A Generalization of Association-Rule Mining.</name><name>BIRCH: An Efficient Data Clustering Method for Very Large Databases.</name></citation><abstract></abstract></paper><paper><title>Design and Implementation of a Genetic-Based Algorithm for Data Mining.</title><author><AuthorName>Sunil Choenni</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><year>2000</year><conference>International Conference on Very Large Data Bases</conference><citation><name>An Interval Classifier for Database Mining Applications.</name><name>Database Mining: A Performance Perspective.</name><name>Learning First Order Logic Rules with a Genetic Algorithm.</name><name>Query Optimization to Support Data Mining.</name><name>On the Suitability of Genetic-Based Algorithms for Data Mining.</name><name>Fundamentals of Database Systems.
 Benjamin/Cummings 1989</name><name>A Genetic Algorithm-Based Approach to Data Mining.</name><name>Integrating Multiple Learning Strategies in First Order Logics.</name><name>Knowledge Discovery in Databases: An Attribute-Oriented Approach.</name><name>Architectural Support for Data Mining.</name><name>SPRINT: A Scalable Parallel Classifier for Data Mining.</name><name>Mining Quantitative Association Rules in Large Relational Tables.</name><name></name></citation><abstract></abstract></paper><paper><title>Mining Frequent Itemsets Using Support Constraints.</title><author><AuthorName>Ke Wang</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>Yu He</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>Jiawei Han</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><year>2000</year><conference>International Conference on Very Large Data Bases</conference><citation><name>Mining Association Rules between Sets of Items in Large Databases.</name><name>Fast Algorithms for Mining Association Rules in Large Databases.</name><name>A New Framework For Itemset Generation.</name><name>Beyond Market Baskets: Generalizing Association Rules to Correlations.</name><name>Dynamic Itemset Counting and Implication Rules for Market Basket Data.</name><name>Finding Interesting Associations without Support Pruning.</name><name>Efficient Mining of Emerging Patterns: Discovering Trends and Differences.</name><name>Discovery of Multiple-Level Association Rules from Large Databases.</name><name>Mining Frequent Patterns without Candidate Generation.</name><name>Integrating Classification and Association Rule Mining.</name><name>Mining Association Rules with Multiple Minimum Supports.</name><name>Mining Audit Data to Build Intrusion Detection Models.</name><name>Extending Na&amp;iuml;ve Bayes Classifiers Using Long Itemsets.</name><name>Efficient Algorithms for Discovering Association Rules.</name><name>An Effective Hash Based Algorithm for Mining Association Rules.</name><name>Search through Systematic Set Enumeration.</name><name>Mining Generalized Association Rules.</name><name>Scalable Techniques for Mining Causal Structures.</name><name>An Efficient Algorithm for Mining Association Rules in Large Databases.</name><name>Mining Association Rules with Item Constraints.</name><name>Building Hierarchical Classifiers Using Class Proximity.</name></citation><abstract></abstract></paper><paper><title>Efficient Filtering of XML Documents for Selective Dissemination of Information.</title><author><AuthorName>Mehmet Altinel</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><author><AuthorName>Michael J. Franklin</AuthorName><institute><InstituteName></InstituteName><country></country></institute></author><year>2000</year><conference>International Conference on Very Large Data Bases</conference><citation><name>Research in Data Broadcast and Dissemination.</name><name>DBIS-Toolkit: Adaptable Middleware for Large Scale Data Delivery.</name><name>The Lorel Query Language for Semistructured Data.</name><name>Information Filtering and Information Retrieval: Two Sides of the Same Coin?</name><name>A Query Language and Optimization Techniques for Unstructured Data.</name><name>Integrating Contents and Structure in Text Retrieval.</name><name>Extensible Markup Language (XML).</name><name>Representing and Querying Changes in Semistructured Data.</name><name>NiagaraCQ: A Scalable Continuous Query System for Internet Databases.</name><name>Self-Adaptive User Profiles for Large-Scale Data Delivery.</name><name>The SGML/XML Web Page.</name><name>Xml-ql: A Query Language for XML.</name><name>"Data In Your Face": Push Technology in Perspective.</name><name>Personalized Information Delivery: An Analysis of Information Filtering Methods.</name><name>Scalable Trigger Processing.</name><name>Continual Queries for Internet Scale Event-Driven Information Delivery.</name><name>The Architecture Of An Active Data Base Management System.</name><name>Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer.