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The purpose of this course is to examine the way computers can help humans deal with knowledge more effectively. It will explore various aspects of dealing with knowledge contained in computer-based repositories. Textbooks, for example, are traditional repositories of knowledge, relying on text, diagrams, and images as the most often used knowledge presentation techniques. Computers offer several additional venues to present knowledge, such as multimedia (e.g. videos), non-static diagrams and images, and interactive exercises and models. At the core of this course is the investigation of fundamental methods for dealing with knowledge through computers, and the analysis and evaluation of specific computer-based tools for the acquisition, organization, and presentation of knowledge. It consists of 3 lecture and 1 laboratory unit. CSC 481 (Knowledge-Based Systems) and graduate standing, or consent of the instructor.
Lecture: Tue, Thu 4:40 - 6:00 in 14-232B, Lab: 6:10 - 7:30 in 14-303
Dr. Franz J. Kurfess
Office hours: Tue, Thu 3:10 - 4:00, Wed 2:10-5:00
Office: 14-218, Phone 756-7179,
Email fkurfess@csc.calpoly.edu
The goal of the course is to understand important problems, challenges, concepts and techniques dealing with the organization and management of knowledge with the help of computers. Upon satisfactory completion of this course, students are expected to:
In order to achieve these goals, students learn how to analyse, design, implement and evaluate programs and systems of varying complexities. The core aspect of these systems is to offer support to "knowledge workers", in particular with respect to the ever-increasing amount of knowledge and information that becomes available and necessary for many tasks. This includes support for traditional tasks related to knowledge management, such as the grouping of related documents into categories or hierarchies, the generation of dictionaries and ontologies, or the construction of knowledge networks through references and citations.
In addition, methods and techniques that rely heavily on features offered by computer-based systems can be used to augment the human-centered tasks. Examples for such approaches are collaborative filtering, automatic content- and usage-based categorization of documents, the categorization of non-textual information such as images, drawings or sound, or the extraction of relevant keywords from documents.
In contrast to knowledge-based systems, where computers are actively involved in the manipulation and generation of knowledge, the goal here is to use computers as tools for activities mainly performed or directed by humans.
To the best of my knowledge, there are no suitable textbooks available for this course. Most of the books and articles on "knowledge management" are written with a business perspective, usually concentrating on the role of knowledge in corporations. Textbooks on Knowledge-based Systems and Artificial Intelligence mostly concentrate on the direct representation and manipulation of knowledge through computers, rather than on the support that computers can offer for human-centered knowledge management.
Further material will be made through pointers to relevant Web pages. A collection of interesting items that I have encountered over the last few years is available as a Google notebook KM Nuggets. You may find additional material in the respective Google notebooks for the AI and HCI classes: AI Nuggets and HCI Nuggets.
The files with the PowerPoint slides will be made available via the course schedule.
Blackboard will be used for some administrative aspects of this class, such as distribution and submission of assignments, and for grading. We will also explore alternatives to Blackboard (such as TRAC wikis), in particular for the team projects and research papers.
This class will rely on interactive classroom activities, such as participation in group discussions, presentation of ideas and results (from textbook, class or assignments), leading discussions on selected readings, providing written summary materials (e.g. via Blackboard or other tools), etc. Success in this class depends on regular attendance, preparation of assigned readings and homework exercises, as well as a level of professionalism in the class presentations. Peer evaluations of papers and presentations may be included as part of the grade. We will try to establish more concrete evaluation criteria for participation in class.
My general policy for late submissions is a penalty of 10% per late business day. If there are situations where you have difficulties meeting a deadline, it is better to contact me in advance in order to discuss possible solutions.
Much of the graded work in this class depends strongly on presentations. Once a team or individual has committed to a date for the presentation, extensions or changes in the dates will only be permitted for documented medical or emergency reasons. With my approval, students may swap presentations.
Activity | Percentage |
---|---|
Assignments | 30% |
Research Presentation and Paper | 30% |
Team Project | 30% |
Class Participation | 10% |
This table gives an overview of the calculation of the grades. I reserve the right, however, to change the formula used. Please note that the project consists of several parts, which will be evaluated separately. With my approval, the topics for the assignments and the presentation/paper may be coordinated with your project topic. The project will be done in teams, and the performance of the team as a whole will be graded unless there is a clear disparity in the contributions of the individual team members. Should this be the case, I might ask for additional documentation like source code, work sheets, email messages, or draft copies of documentation to evaluate individual contributions.
FJK Home | CPE/CSC 581 | Syllabus | Schedule | Lecture Notes | Assignments | Paper | Project | Teams |
Franz J. Kurfess |