Vision + Focus + Execution

Meiliu Lu, RVR 5016, mlu@csus.edu

http://gaia.ecs.csus.edu/~mei/

For CSc 209 Spring 2003, 5/6/03

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Outline Vision: know what is going to

happen Focus: Interests – key elements to

keep you going, select project topic

Execution: methodology Take a look at how others have done Prepare, start, and finish yours

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R. W. Hamming on R & D What can happen Science What will happen engineering &

economics What should happen morals,

ethics and including what society is prepared to accept and reject

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Richard M. Karp’s 3 Principles on Making Career Decisions Understand what you are good at and what

you like to do, and choose accordingly. In the words of Socrates, “Know thyself.”

Disregard the fashions of the day and search for new areas of research that are about to become important. In the words of the great hockey player and philosopher Wayne Gretzky, “Skate to where the puck is gonna be.”

To find exciting problems, look at the interfaces between disciplines.

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Research Interests and Projects

Machine learning and data mining DMV Data mining (clustering and data

warehousing, OLAP) Data management and integration

Web portal development (Searchware) Data integration and visualization (multiple data

sources and single analytical view) Courseware Development

XML course module (136) Data Warehousing course module (196K) SVM, support vector machine (196K, 219)

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Select Project Topic Select a topic according to your

interest and factors such as following: Utility vs. innovation Learning Timing

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What is Data Mining? Data mining, simulation, and modeling

are part of a large process – Knowledge Discovery in Data (KDD)

Finding hidden information in a database

Fit data to a model Web related data Business, health, and financial data Scientific and Engineering

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Data Mining Algorithms Objective: fit data to a model

Descriptive Predictive

Preference – technique to choose the best model

Search – technique to search the data “Query”

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Query Examples Database

Find all credit applications with last name of smith

Identify customers who have purchased more than $10,000 in the last month.

Find all customers who have purchased milk

Data mining Find all credit

applicants who are poor credit risks. (classification)

Identify customers with similar buying habits. (clustering)

Find all item which are frequently purchased with milk. (association rules)

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Extracting Knowledge from Gene Expression Data: A Case Study of Batten Disease – S. M. Lin

Duke University Medical Center proposed a prototype KDD system to enable scientists to analyze the massive microarray data, form hypotheses, and draw insights directly into underlying mechanisms of diseases.

Data Microarray database data mining patterns human experts Genomics knowledge base discoveries

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Your MS Project Try to make someone happy

yourself people who helped you people who need help

Start early, keep working, finish on time

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Sample MS Project 1 Jeffery Lewis, Spring 2001, “Audio

Compression for Music Synthesis Using Gaussion Functions and Genetic Algorithms”

Paper published in the proceedings of 3rd International Conference on Information Reuse and Integration. November 2001

Self-selected topic

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Sample MS Project 2 Yan Xiong, Summer 2002, “A Web-

Based Microarray Management System” Paper published in the 15th

International Conference on Computer Applications in Industry and Engineering. November 2002.

Topic introduced at CSC 209 Fall 2001 Improvement: engineering and function

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Sample MS Project 3 Wen Xia, Fall 2002, “Online Course

Management System” Developed for C Sc 138 and can be

adopted for other courses Topic selected by self (continue

development of an existing tool) More system enhancement can be

a new MS project

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Writing Report

“MS Thesis and Project Writing Guide” at: http://gaia.ecs.csus.edu/~mei/

Format, References and Acknowledgement

A useful reference book: “Writing for Computer Science” by Justin Zobel, Springer, 1998.

Game of time and stepping stone

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Leaders are VisionariesDr. Ernie Bodai

They have a poorly developed sense of fear

They have no concept of the odds against them

They make the impossible happen