Level 1 Papers

Level 2 Papers

Level 3 Papers

Level 4 Papers

Level 5 Papers

Summer School Papers

Industry Papers

Studio Management

Report of an Investigation

Topics in Operating Systems

Topics in Computer Networks

Machine Learning Algorithms

Data Stream Mining

Usability Engineering

Web Search: Technical and Social Issues

Developing Mobile Applications

Location-Based Systems as Context-Aware Systems

Model Checking

Extremely Parallel Programming

Turing Topics


Control Theory and Image Processing

2014 Papers
Level 5 Papers >> A Semester
COMP523A Data Stream Mining

15 Points

Data streams are everywhere, from F1 racing over electricity networks to news feeds. Data stream mining relies on and develops new incremental algorithms that process streams under strict resource limitations. This paper focuses on, as well as extends the methods implemented in MOA, an open source stream mining software suite currently being developed by the Machine Learning group.

Learning Outcomes
Students will learn to how select and apply an appropriate method for a given data stream problem; they will learn how to design and implement such algorithms in frameworks like MOA; they will learn how to evaluate and compare different solutions, and how to summarize their findings in a report; they will learn how to select published research and replicate it.

Pre Requisite Papers
Three 300 level Computer Science papers, including
COMP321 Practical Data Mining or
COMP316 Artificial Intelligence Techniques and Applications

Corresponding Papers
COMP423 Data Stream Mining

Lecturers and Tutors

A Semester

Moodle Link
Moodle COMP423/523

Official Timetable Information

Compulsory Components
All items of assessment are compulsory, except for class attendance. Detailed assessment info is given on the Moodle page for this course.

10 hours/week.

Required Reading
Joao Gama: Knowledge Discovery from Data Streams

Assessment Ratio
Internal assessment/final examination ratio 1:0

Assessment Components
see Moodle page for details

Assessment Deadlines
see Moodle page for details

Hand in and Return of Assignments
online through Moodle

Attendance Policy
Class attendance is expected. The course notes provided are not comprehensive, additional material will be covered in class. You are responsible for all material covered in class.

Changes in Response to Course Evaluations
Added a mid-term test, test times reduced two a single hour.

Academic Integrity
Follow this link for Academic Integrity information.

Performance Impairment
Follow this link for information on Performance Impairment.

Student Concerns and Complaints
Follow this link for Student Concerns and Complaints information.

Application for Extension
Follow this link for information on applying for an Extension.

Review of Grade
Follow this link for information on applying for a Review of Grade.

University Regulations
Your attention is drawn to the following regulations and policies, which are published in the University Calendar:

  2007 FCMS. The University of Waikato - Te Whare Wananga o Waikato