Class Lectures


  1. Course Description and Introduction to Data Mining
    Overview of CS590D
    Tuesday, January 13, 1998


    Database Perspectives on Data Mining

    The next few lectures will concentrate on the interplay between database systems and data mining. There are several issues that have been studied by researchers on how to to enhance database support for data mining. They can be broadly classified as:

    1. Enhancing the underlying model of data and DBMSs (The Logical Model of Data, Deductive Databases, Rules, Active Databases, Semistructured data, SDDF etc.)
    2. Enhancing the expressiveness of query languages (Rule Query Languages, Meta Queries, Query optimizations)
    3. Integration with Data Warehousing Systems (OLAP, Historical Data, Meta-Data, Interactive Exploring)

    Of course, there are 3Cn combinations of these ideas, too.


  2. Database Perspectives on Data Mining (1)
    Introduction to Deductive Databases
    Thursday, January 15, 1998

  3. Database Perspectives on Data Mining (2)
    Introduction to PROLOG and ILP systems
    Tuesday, January 20, 1998

  4. Database Perspectives on Data Mining (3)
    Enhancing the expressiveness of query languages
    Thursday, January 22, 1998

  5. Database Perspectives on Data Mining (4)
    Data Warehousing, OLAP etc.
    Tuesday, January 27, 1998

  6. Database Perspectives (Misc. Themes)
    Associations, Rule Generation
    Thursday, January 29, 1998


    Statistical Perspectives on Data Mining

    The next few classes will concentrate on the many different statistical viewpoints that have been offered for the data miner. In particular, we focus on issues in small and large sample size statistics, models and perspectives from statistical learning theory, as applied to data mining.


  7. Introduction
    Overview, Main Themes
    Tuesday, February 3, 1998

  8. A Tutorial on Neural Networks
    More Statistical Perspectives
    Thursday, February 5, 1998


    Perspectives from the AI community

    The distinction of lectures here is not very crisp here, but the following topics will form a smooth transition from the statistical viewpoints to ones offered by the AI researcher. This mostly involves what is known as "speedup" learning by the machine learning community.


  9. Classification
    Machine Learning Algorithms
    Tuesday, February 10, 1998

  10. More ML algorithms
    Miscellaneous algorithms proposed by the AI community
    Thursday, February 12, 1998

  11. Genetic Algorithms in Data Mining
    Introduction to Genetic Operators, Algorithms etc.
    Tuesday, February 17, 1998


    Algorithmic Aspects (Time Series Analysis, Association Rules and Mining)


  12. Time series analysis
    Tuesday, February 24, 1998

  13. Time series analysis (matching templates)
    Thursday, February 26, 1998

  14. Algorithms for Associations
    Tuesday, March 3, 1998

  15. More on Associations
    Thursday, March 5, 1998

  16. Algorithms and Strategies for Similarity Retrieval
    Tuesday, March 17, 1998

  17. Clustering In A High-Dimensional Space Using Hypergraph Models and
    Data Mining. Hypergraph Traversals, and Machine Learning

    Thursday, March 19, 1998

  18. Beyond Market Baskets: Generalizing Association Rules to Correlations
    Lecture Slides
    Thursday, March 26, 1998

  19. Beyond Market Baskets: Generalizing Association Rules to Correlations (Contd.)
    Lecture Slides
    Tuesday, March 31, 1998


    Mining the Web


  20. Mining the WWW
    Introduction and Main Themes
    Thursday, April 2, 1998

  21. Indexing by latent semantic analysis
    Mon Apr 6 22:04:11 EST 1998


    Parallelism in Data Mining


  22. Parallel Formulations of Decision-Tree Classification Algorithms and ScalParC: A New Scalable and Efficient Parallel Classification Algorithm for Mining Large Datasets
    Wed Apr 8 18:40:00 EST 1998

  23. Parallel Data Mining for Association Rules on Shared-memory Multi-processors
    Tue Apr 14 08:11:36 EST 1998

  24. Towards a Cost-Effective Parallel Data Mining Approach
    Thu Apr 16 11:17:54 EST 1998

  25. Visualizing data mining results.
    Mon Apr 20 22:47:50 EST 1998


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