IST 511: Information Management – Information and Technology

Location and Time:

Tuesday: 11:15 AM - 2:15 PM, IST 202.

Lee Giles office hrs at IST311A: Tuesday 2:30-3:30 PM, Wednesday 1:30-2:30 PM or by appointment.

Anne Ya Zhang office hrs at IST313D: Monday 4:00-5:30 PM, Thursday 11:00 AM - 12:30 PM.

Premise of the Course:

This lecture and project based course is an introduction to computational (formal) methods for information generation, modeling, transmission, processing and analysis. This semester this course will approach information management primarily from a knowledge managment perspective. Students will use the methodologies introduced in example problems and applications, but no formal proofs will be expected. A collection of methods will be introduced, most of which are algorithmic and explore the links between the critical constructs of information science and technology across the various theoretical bases. As such, these methods have applications in all areas of information, computational, cognitive and social sciences from intelligent information processing to human computer interfaces to social networks. This course introduces methods applicable to all these domains. Research issues related to these topics will be discussed where appropriate.

Topics covered will include but not limited to formal models of information such as information theory, information representation and transmission, information sampling and data presentation and storage, formal grammars and language, information compression and encryption, information complexity, graphs and networks, pattern recognition, knowledge representation and management, data mining and inference, and information retrieval. Other topics could be covered.

Grading:

Students will be assigned a problem-oriented term project (50%) and exercises (20%) in the areas covered which will be worth 70% of the final grade. Students will also take a final exam worth 30% of the final grade. Exercises and projects are due when specified. Late Policy: Starting right after the required submission date of any exercise, 1/3 of the grade will be deducted for everyday tardy until no grade is available.

Unless otherwise specified, projects and exercises are individual and not group projects. Please see the academic integrity policy for more details.

Prerequisites: Prior understanding of the fundamentals of information sciences such as databases, discrete mathematics, programming, algorithms and statistics is greatly encouraged but not necessary.

Schedule:

This schedule is subject to change. Please check it on a regular basis for assignments. Some classes will have online handouts. It is the student’s responsibility to download that material.

Course Materials and References:

Here is a link to the text, some course materials and references. There could also be links under the schedule.

Acknowledgements: